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  • v.37(16); 2022 Apr 25

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A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles

Edward barroga.

1 Department of General Education, Graduate School of Nursing Science, St. Luke’s International University, Tokyo, Japan.

Glafera Janet Matanguihan

2 Department of Biological Sciences, Messiah University, Mechanicsburg, PA, USA.

The development of research questions and the subsequent hypotheses are prerequisites to defining the main research purpose and specific objectives of a study. Consequently, these objectives determine the study design and research outcome. The development of research questions is a process based on knowledge of current trends, cutting-edge studies, and technological advances in the research field. Excellent research questions are focused and require a comprehensive literature search and in-depth understanding of the problem being investigated. Initially, research questions may be written as descriptive questions which could be developed into inferential questions. These questions must be specific and concise to provide a clear foundation for developing hypotheses. Hypotheses are more formal predictions about the research outcomes. These specify the possible results that may or may not be expected regarding the relationship between groups. Thus, research questions and hypotheses clarify the main purpose and specific objectives of the study, which in turn dictate the design of the study, its direction, and outcome. Studies developed from good research questions and hypotheses will have trustworthy outcomes with wide-ranging social and health implications.

INTRODUCTION

Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses. 1 , 2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results. 3 , 4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the inception of novel studies and the ethical testing of ideas. 5 , 6

It is crucial to have knowledge of both quantitative and qualitative research 2 as both types of research involve writing research questions and hypotheses. 7 However, these crucial elements of research are sometimes overlooked; if not overlooked, then framed without the forethought and meticulous attention it needs. Planning and careful consideration are needed when developing quantitative or qualitative research, particularly when conceptualizing research questions and hypotheses. 4

There is a continuing need to support researchers in the creation of innovative research questions and hypotheses, as well as for journal articles that carefully review these elements. 1 When research questions and hypotheses are not carefully thought of, unethical studies and poor outcomes usually ensue. Carefully formulated research questions and hypotheses define well-founded objectives, which in turn determine the appropriate design, course, and outcome of the study. This article then aims to discuss in detail the various aspects of crafting research questions and hypotheses, with the goal of guiding researchers as they develop their own. Examples from the authors and peer-reviewed scientific articles in the healthcare field are provided to illustrate key points.

DEFINITIONS AND RELATIONSHIP OF RESEARCH QUESTIONS AND HYPOTHESES

A research question is what a study aims to answer after data analysis and interpretation. The answer is written in length in the discussion section of the paper. Thus, the research question gives a preview of the different parts and variables of the study meant to address the problem posed in the research question. 1 An excellent research question clarifies the research writing while facilitating understanding of the research topic, objective, scope, and limitations of the study. 5

On the other hand, a research hypothesis is an educated statement of an expected outcome. This statement is based on background research and current knowledge. 8 , 9 The research hypothesis makes a specific prediction about a new phenomenon 10 or a formal statement on the expected relationship between an independent variable and a dependent variable. 3 , 11 It provides a tentative answer to the research question to be tested or explored. 4

Hypotheses employ reasoning to predict a theory-based outcome. 10 These can also be developed from theories by focusing on components of theories that have not yet been observed. 10 The validity of hypotheses is often based on the testability of the prediction made in a reproducible experiment. 8

Conversely, hypotheses can also be rephrased as research questions. Several hypotheses based on existing theories and knowledge may be needed to answer a research question. Developing ethical research questions and hypotheses creates a research design that has logical relationships among variables. These relationships serve as a solid foundation for the conduct of the study. 4 , 11 Haphazardly constructed research questions can result in poorly formulated hypotheses and improper study designs, leading to unreliable results. Thus, the formulations of relevant research questions and verifiable hypotheses are crucial when beginning research. 12

CHARACTERISTICS OF GOOD RESEARCH QUESTIONS AND HYPOTHESES

Excellent research questions are specific and focused. These integrate collective data and observations to confirm or refute the subsequent hypotheses. Well-constructed hypotheses are based on previous reports and verify the research context. These are realistic, in-depth, sufficiently complex, and reproducible. More importantly, these hypotheses can be addressed and tested. 13

There are several characteristics of well-developed hypotheses. Good hypotheses are 1) empirically testable 7 , 10 , 11 , 13 ; 2) backed by preliminary evidence 9 ; 3) testable by ethical research 7 , 9 ; 4) based on original ideas 9 ; 5) have evidenced-based logical reasoning 10 ; and 6) can be predicted. 11 Good hypotheses can infer ethical and positive implications, indicating the presence of a relationship or effect relevant to the research theme. 7 , 11 These are initially developed from a general theory and branch into specific hypotheses by deductive reasoning. In the absence of a theory to base the hypotheses, inductive reasoning based on specific observations or findings form more general hypotheses. 10

TYPES OF RESEARCH QUESTIONS AND HYPOTHESES

Research questions and hypotheses are developed according to the type of research, which can be broadly classified into quantitative and qualitative research. We provide a summary of the types of research questions and hypotheses under quantitative and qualitative research categories in Table 1 .

Research questions in quantitative research

In quantitative research, research questions inquire about the relationships among variables being investigated and are usually framed at the start of the study. These are precise and typically linked to the subject population, dependent and independent variables, and research design. 1 Research questions may also attempt to describe the behavior of a population in relation to one or more variables, or describe the characteristics of variables to be measured ( descriptive research questions ). 1 , 5 , 14 These questions may also aim to discover differences between groups within the context of an outcome variable ( comparative research questions ), 1 , 5 , 14 or elucidate trends and interactions among variables ( relationship research questions ). 1 , 5 We provide examples of descriptive, comparative, and relationship research questions in quantitative research in Table 2 .

Hypotheses in quantitative research

In quantitative research, hypotheses predict the expected relationships among variables. 15 Relationships among variables that can be predicted include 1) between a single dependent variable and a single independent variable ( simple hypothesis ) or 2) between two or more independent and dependent variables ( complex hypothesis ). 4 , 11 Hypotheses may also specify the expected direction to be followed and imply an intellectual commitment to a particular outcome ( directional hypothesis ) 4 . On the other hand, hypotheses may not predict the exact direction and are used in the absence of a theory, or when findings contradict previous studies ( non-directional hypothesis ). 4 In addition, hypotheses can 1) define interdependency between variables ( associative hypothesis ), 4 2) propose an effect on the dependent variable from manipulation of the independent variable ( causal hypothesis ), 4 3) state a negative relationship between two variables ( null hypothesis ), 4 , 11 , 15 4) replace the working hypothesis if rejected ( alternative hypothesis ), 15 explain the relationship of phenomena to possibly generate a theory ( working hypothesis ), 11 5) involve quantifiable variables that can be tested statistically ( statistical hypothesis ), 11 6) or express a relationship whose interlinks can be verified logically ( logical hypothesis ). 11 We provide examples of simple, complex, directional, non-directional, associative, causal, null, alternative, working, statistical, and logical hypotheses in quantitative research, as well as the definition of quantitative hypothesis-testing research in Table 3 .

Research questions in qualitative research

Unlike research questions in quantitative research, research questions in qualitative research are usually continuously reviewed and reformulated. The central question and associated subquestions are stated more than the hypotheses. 15 The central question broadly explores a complex set of factors surrounding the central phenomenon, aiming to present the varied perspectives of participants. 15

There are varied goals for which qualitative research questions are developed. These questions can function in several ways, such as to 1) identify and describe existing conditions ( contextual research question s); 2) describe a phenomenon ( descriptive research questions ); 3) assess the effectiveness of existing methods, protocols, theories, or procedures ( evaluation research questions ); 4) examine a phenomenon or analyze the reasons or relationships between subjects or phenomena ( explanatory research questions ); or 5) focus on unknown aspects of a particular topic ( exploratory research questions ). 5 In addition, some qualitative research questions provide new ideas for the development of theories and actions ( generative research questions ) or advance specific ideologies of a position ( ideological research questions ). 1 Other qualitative research questions may build on a body of existing literature and become working guidelines ( ethnographic research questions ). Research questions may also be broadly stated without specific reference to the existing literature or a typology of questions ( phenomenological research questions ), may be directed towards generating a theory of some process ( grounded theory questions ), or may address a description of the case and the emerging themes ( qualitative case study questions ). 15 We provide examples of contextual, descriptive, evaluation, explanatory, exploratory, generative, ideological, ethnographic, phenomenological, grounded theory, and qualitative case study research questions in qualitative research in Table 4 , and the definition of qualitative hypothesis-generating research in Table 5 .

Qualitative studies usually pose at least one central research question and several subquestions starting with How or What . These research questions use exploratory verbs such as explore or describe . These also focus on one central phenomenon of interest, and may mention the participants and research site. 15

Hypotheses in qualitative research

Hypotheses in qualitative research are stated in the form of a clear statement concerning the problem to be investigated. Unlike in quantitative research where hypotheses are usually developed to be tested, qualitative research can lead to both hypothesis-testing and hypothesis-generating outcomes. 2 When studies require both quantitative and qualitative research questions, this suggests an integrative process between both research methods wherein a single mixed-methods research question can be developed. 1

FRAMEWORKS FOR DEVELOPING RESEARCH QUESTIONS AND HYPOTHESES

Research questions followed by hypotheses should be developed before the start of the study. 1 , 12 , 14 It is crucial to develop feasible research questions on a topic that is interesting to both the researcher and the scientific community. This can be achieved by a meticulous review of previous and current studies to establish a novel topic. Specific areas are subsequently focused on to generate ethical research questions. The relevance of the research questions is evaluated in terms of clarity of the resulting data, specificity of the methodology, objectivity of the outcome, depth of the research, and impact of the study. 1 , 5 These aspects constitute the FINER criteria (i.e., Feasible, Interesting, Novel, Ethical, and Relevant). 1 Clarity and effectiveness are achieved if research questions meet the FINER criteria. In addition to the FINER criteria, Ratan et al. described focus, complexity, novelty, feasibility, and measurability for evaluating the effectiveness of research questions. 14

The PICOT and PEO frameworks are also used when developing research questions. 1 The following elements are addressed in these frameworks, PICOT: P-population/patients/problem, I-intervention or indicator being studied, C-comparison group, O-outcome of interest, and T-timeframe of the study; PEO: P-population being studied, E-exposure to preexisting conditions, and O-outcome of interest. 1 Research questions are also considered good if these meet the “FINERMAPS” framework: Feasible, Interesting, Novel, Ethical, Relevant, Manageable, Appropriate, Potential value/publishable, and Systematic. 14

As we indicated earlier, research questions and hypotheses that are not carefully formulated result in unethical studies or poor outcomes. To illustrate this, we provide some examples of ambiguous research question and hypotheses that result in unclear and weak research objectives in quantitative research ( Table 6 ) 16 and qualitative research ( Table 7 ) 17 , and how to transform these ambiguous research question(s) and hypothesis(es) into clear and good statements.

a These statements were composed for comparison and illustrative purposes only.

b These statements are direct quotes from Higashihara and Horiuchi. 16

a This statement is a direct quote from Shimoda et al. 17

The other statements were composed for comparison and illustrative purposes only.

CONSTRUCTING RESEARCH QUESTIONS AND HYPOTHESES

To construct effective research questions and hypotheses, it is very important to 1) clarify the background and 2) identify the research problem at the outset of the research, within a specific timeframe. 9 Then, 3) review or conduct preliminary research to collect all available knowledge about the possible research questions by studying theories and previous studies. 18 Afterwards, 4) construct research questions to investigate the research problem. Identify variables to be accessed from the research questions 4 and make operational definitions of constructs from the research problem and questions. Thereafter, 5) construct specific deductive or inductive predictions in the form of hypotheses. 4 Finally, 6) state the study aims . This general flow for constructing effective research questions and hypotheses prior to conducting research is shown in Fig. 1 .

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Research questions are used more frequently in qualitative research than objectives or hypotheses. 3 These questions seek to discover, understand, explore or describe experiences by asking “What” or “How.” The questions are open-ended to elicit a description rather than to relate variables or compare groups. The questions are continually reviewed, reformulated, and changed during the qualitative study. 3 Research questions are also used more frequently in survey projects than hypotheses in experiments in quantitative research to compare variables and their relationships.

Hypotheses are constructed based on the variables identified and as an if-then statement, following the template, ‘If a specific action is taken, then a certain outcome is expected.’ At this stage, some ideas regarding expectations from the research to be conducted must be drawn. 18 Then, the variables to be manipulated (independent) and influenced (dependent) are defined. 4 Thereafter, the hypothesis is stated and refined, and reproducible data tailored to the hypothesis are identified, collected, and analyzed. 4 The hypotheses must be testable and specific, 18 and should describe the variables and their relationships, the specific group being studied, and the predicted research outcome. 18 Hypotheses construction involves a testable proposition to be deduced from theory, and independent and dependent variables to be separated and measured separately. 3 Therefore, good hypotheses must be based on good research questions constructed at the start of a study or trial. 12

In summary, research questions are constructed after establishing the background of the study. Hypotheses are then developed based on the research questions. Thus, it is crucial to have excellent research questions to generate superior hypotheses. In turn, these would determine the research objectives and the design of the study, and ultimately, the outcome of the research. 12 Algorithms for building research questions and hypotheses are shown in Fig. 2 for quantitative research and in Fig. 3 for qualitative research.

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EXAMPLES OF RESEARCH QUESTIONS FROM PUBLISHED ARTICLES

  • EXAMPLE 1. Descriptive research question (quantitative research)
  • - Presents research variables to be assessed (distinct phenotypes and subphenotypes)
  • “BACKGROUND: Since COVID-19 was identified, its clinical and biological heterogeneity has been recognized. Identifying COVID-19 phenotypes might help guide basic, clinical, and translational research efforts.
  • RESEARCH QUESTION: Does the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes? ” 19
  • EXAMPLE 2. Relationship research question (quantitative research)
  • - Shows interactions between dependent variable (static postural control) and independent variable (peripheral visual field loss)
  • “Background: Integration of visual, vestibular, and proprioceptive sensations contributes to postural control. People with peripheral visual field loss have serious postural instability. However, the directional specificity of postural stability and sensory reweighting caused by gradual peripheral visual field loss remain unclear.
  • Research question: What are the effects of peripheral visual field loss on static postural control ?” 20
  • EXAMPLE 3. Comparative research question (quantitative research)
  • - Clarifies the difference among groups with an outcome variable (patients enrolled in COMPERA with moderate PH or severe PH in COPD) and another group without the outcome variable (patients with idiopathic pulmonary arterial hypertension (IPAH))
  • “BACKGROUND: Pulmonary hypertension (PH) in COPD is a poorly investigated clinical condition.
  • RESEARCH QUESTION: Which factors determine the outcome of PH in COPD?
  • STUDY DESIGN AND METHODS: We analyzed the characteristics and outcome of patients enrolled in the Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension (COMPERA) with moderate or severe PH in COPD as defined during the 6th PH World Symposium who received medical therapy for PH and compared them with patients with idiopathic pulmonary arterial hypertension (IPAH) .” 21
  • EXAMPLE 4. Exploratory research question (qualitative research)
  • - Explores areas that have not been fully investigated (perspectives of families and children who receive care in clinic-based child obesity treatment) to have a deeper understanding of the research problem
  • “Problem: Interventions for children with obesity lead to only modest improvements in BMI and long-term outcomes, and data are limited on the perspectives of families of children with obesity in clinic-based treatment. This scoping review seeks to answer the question: What is known about the perspectives of families and children who receive care in clinic-based child obesity treatment? This review aims to explore the scope of perspectives reported by families of children with obesity who have received individualized outpatient clinic-based obesity treatment.” 22
  • EXAMPLE 5. Relationship research question (quantitative research)
  • - Defines interactions between dependent variable (use of ankle strategies) and independent variable (changes in muscle tone)
  • “Background: To maintain an upright standing posture against external disturbances, the human body mainly employs two types of postural control strategies: “ankle strategy” and “hip strategy.” While it has been reported that the magnitude of the disturbance alters the use of postural control strategies, it has not been elucidated how the level of muscle tone, one of the crucial parameters of bodily function, determines the use of each strategy. We have previously confirmed using forward dynamics simulations of human musculoskeletal models that an increased muscle tone promotes the use of ankle strategies. The objective of the present study was to experimentally evaluate a hypothesis: an increased muscle tone promotes the use of ankle strategies. Research question: Do changes in the muscle tone affect the use of ankle strategies ?” 23

EXAMPLES OF HYPOTHESES IN PUBLISHED ARTICLES

  • EXAMPLE 1. Working hypothesis (quantitative research)
  • - A hypothesis that is initially accepted for further research to produce a feasible theory
  • “As fever may have benefit in shortening the duration of viral illness, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response when taken during the early stages of COVID-19 illness .” 24
  • “In conclusion, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response . The difference in perceived safety of these agents in COVID-19 illness could be related to the more potent efficacy to reduce fever with ibuprofen compared to acetaminophen. Compelling data on the benefit of fever warrant further research and review to determine when to treat or withhold ibuprofen for early stage fever for COVID-19 and other related viral illnesses .” 24
  • EXAMPLE 2. Exploratory hypothesis (qualitative research)
  • - Explores particular areas deeper to clarify subjective experience and develop a formal hypothesis potentially testable in a future quantitative approach
  • “We hypothesized that when thinking about a past experience of help-seeking, a self distancing prompt would cause increased help-seeking intentions and more favorable help-seeking outcome expectations .” 25
  • “Conclusion
  • Although a priori hypotheses were not supported, further research is warranted as results indicate the potential for using self-distancing approaches to increasing help-seeking among some people with depressive symptomatology.” 25
  • EXAMPLE 3. Hypothesis-generating research to establish a framework for hypothesis testing (qualitative research)
  • “We hypothesize that compassionate care is beneficial for patients (better outcomes), healthcare systems and payers (lower costs), and healthcare providers (lower burnout). ” 26
  • Compassionomics is the branch of knowledge and scientific study of the effects of compassionate healthcare. Our main hypotheses are that compassionate healthcare is beneficial for (1) patients, by improving clinical outcomes, (2) healthcare systems and payers, by supporting financial sustainability, and (3) HCPs, by lowering burnout and promoting resilience and well-being. The purpose of this paper is to establish a scientific framework for testing the hypotheses above . If these hypotheses are confirmed through rigorous research, compassionomics will belong in the science of evidence-based medicine, with major implications for all healthcare domains.” 26
  • EXAMPLE 4. Statistical hypothesis (quantitative research)
  • - An assumption is made about the relationship among several population characteristics ( gender differences in sociodemographic and clinical characteristics of adults with ADHD ). Validity is tested by statistical experiment or analysis ( chi-square test, Students t-test, and logistic regression analysis)
  • “Our research investigated gender differences in sociodemographic and clinical characteristics of adults with ADHD in a Japanese clinical sample. Due to unique Japanese cultural ideals and expectations of women's behavior that are in opposition to ADHD symptoms, we hypothesized that women with ADHD experience more difficulties and present more dysfunctions than men . We tested the following hypotheses: first, women with ADHD have more comorbidities than men with ADHD; second, women with ADHD experience more social hardships than men, such as having less full-time employment and being more likely to be divorced.” 27
  • “Statistical Analysis
  • ( text omitted ) Between-gender comparisons were made using the chi-squared test for categorical variables and Students t-test for continuous variables…( text omitted ). A logistic regression analysis was performed for employment status, marital status, and comorbidity to evaluate the independent effects of gender on these dependent variables.” 27

EXAMPLES OF HYPOTHESIS AS WRITTEN IN PUBLISHED ARTICLES IN RELATION TO OTHER PARTS

  • EXAMPLE 1. Background, hypotheses, and aims are provided
  • “Pregnant women need skilled care during pregnancy and childbirth, but that skilled care is often delayed in some countries …( text omitted ). The focused antenatal care (FANC) model of WHO recommends that nurses provide information or counseling to all pregnant women …( text omitted ). Job aids are visual support materials that provide the right kind of information using graphics and words in a simple and yet effective manner. When nurses are not highly trained or have many work details to attend to, these job aids can serve as a content reminder for the nurses and can be used for educating their patients (Jennings, Yebadokpo, Affo, & Agbogbe, 2010) ( text omitted ). Importantly, additional evidence is needed to confirm how job aids can further improve the quality of ANC counseling by health workers in maternal care …( text omitted )” 28
  • “ This has led us to hypothesize that the quality of ANC counseling would be better if supported by job aids. Consequently, a better quality of ANC counseling is expected to produce higher levels of awareness concerning the danger signs of pregnancy and a more favorable impression of the caring behavior of nurses .” 28
  • “This study aimed to examine the differences in the responses of pregnant women to a job aid-supported intervention during ANC visit in terms of 1) their understanding of the danger signs of pregnancy and 2) their impression of the caring behaviors of nurses to pregnant women in rural Tanzania.” 28
  • EXAMPLE 2. Background, hypotheses, and aims are provided
  • “We conducted a two-arm randomized controlled trial (RCT) to evaluate and compare changes in salivary cortisol and oxytocin levels of first-time pregnant women between experimental and control groups. The women in the experimental group touched and held an infant for 30 min (experimental intervention protocol), whereas those in the control group watched a DVD movie of an infant (control intervention protocol). The primary outcome was salivary cortisol level and the secondary outcome was salivary oxytocin level.” 29
  • “ We hypothesize that at 30 min after touching and holding an infant, the salivary cortisol level will significantly decrease and the salivary oxytocin level will increase in the experimental group compared with the control group .” 29
  • EXAMPLE 3. Background, aim, and hypothesis are provided
  • “In countries where the maternal mortality ratio remains high, antenatal education to increase Birth Preparedness and Complication Readiness (BPCR) is considered one of the top priorities [1]. BPCR includes birth plans during the antenatal period, such as the birthplace, birth attendant, transportation, health facility for complications, expenses, and birth materials, as well as family coordination to achieve such birth plans. In Tanzania, although increasing, only about half of all pregnant women attend an antenatal clinic more than four times [4]. Moreover, the information provided during antenatal care (ANC) is insufficient. In the resource-poor settings, antenatal group education is a potential approach because of the limited time for individual counseling at antenatal clinics.” 30
  • “This study aimed to evaluate an antenatal group education program among pregnant women and their families with respect to birth-preparedness and maternal and infant outcomes in rural villages of Tanzania.” 30
  • “ The study hypothesis was if Tanzanian pregnant women and their families received a family-oriented antenatal group education, they would (1) have a higher level of BPCR, (2) attend antenatal clinic four or more times, (3) give birth in a health facility, (4) have less complications of women at birth, and (5) have less complications and deaths of infants than those who did not receive the education .” 30

Research questions and hypotheses are crucial components to any type of research, whether quantitative or qualitative. These questions should be developed at the very beginning of the study. Excellent research questions lead to superior hypotheses, which, like a compass, set the direction of research, and can often determine the successful conduct of the study. Many research studies have floundered because the development of research questions and subsequent hypotheses was not given the thought and meticulous attention needed. The development of research questions and hypotheses is an iterative process based on extensive knowledge of the literature and insightful grasp of the knowledge gap. Focused, concise, and specific research questions provide a strong foundation for constructing hypotheses which serve as formal predictions about the research outcomes. Research questions and hypotheses are crucial elements of research that should not be overlooked. They should be carefully thought of and constructed when planning research. This avoids unethical studies and poor outcomes by defining well-founded objectives that determine the design, course, and outcome of the study.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

  • Conceptualization: Barroga E, Matanguihan GJ.
  • Methodology: Barroga E, Matanguihan GJ.
  • Writing - original draft: Barroga E, Matanguihan GJ.
  • Writing - review & editing: Barroga E, Matanguihan GJ.
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How to Write Quantitative Research Questions: Types With Examples

How to Write Quantitative Research Questions: Types With Examples

For research to be effective, it becomes crucial to properly formulate the quantitative research questions in a correct way. Otherwise, you will not get the answers you were looking for.

Has it ever happened that you conducted a quantitative research study and found out the results you were expecting are quite different from the actual results?

This could happen due to many factors like the unpredictable nature of respondents, errors in calculation, research bias, etc. However, your quantitative research usually does not provide reliable results when questions are not written correctly.

We get it! Structuring the quantitative research questions can be a difficult task.

Hence, in this blog, we will share a few bits of advice on how to write good quantitative research questions. We will also look at different types of quantitative research questions along with their examples.

Let’s start:

How to Write Quantitative Research Questions?

When you want to obtain actionable insight into the trends and patterns of the research topic to make sense of it, quantitative research questions are your best bet.

Being objective in nature, these questions provide you with detailed information about the research topic and help in collecting quantifiable data that can be easily analyzed. This data can be generalized to the entire population and help make data-driven and sound decisions.

Respondents find it easier to answer quantitative survey questions than qualitative questions . At the same time, researchers can also analyze them quickly using various statistical models.

However, when it comes to writing the quantitative research questions, one can get a little overwhelmed as the entire study depends on the types of questions used.

There is no “one good way” to prepare these questions. However, to design well-structured quantitative research questions, you can follow the 4-steps approach given below:

1. Select the Type of Quantitative Question

The first step is to determine which type of quantitative question you want to add to your study. There are three types of quantitative questions:

  • Descriptive
  • Comparative 
  • Relationship-based

This will help you choose the correct words and phrases while constructing the question. At the same time, it will also assist readers in understanding the question correctly.

2. Identify the Type of Variable

The second step involves identifying the type of variable you are trying to measure, manipulate, or control. Basically, there are two types of variables:

  • Independent variable (a variable that is being manipulated)
  • Dependent variable (outcome variable)

quantitative questions examples

If you plan to use descriptive research questions, you have to deal with a number of dependent variables. However, where you plan to create comparative or relationship research questions, you will deal with both dependent and independent variables.

3. Select the Suitable Structure

The next step is determining the structure of the research question. It involves:

  • Identifying the components of the question. It involves the type of dependent or independent variable and a group of interest (the group from which the researcher tries to conclude the population).
  • The number of different components used. Like, as to how many variables and groups are being examined.
  • Order in which these are presented. For example, the independent variable before the dependent variable or vice versa.

4. Draft the Complete Research Question

The last step involves identifying the problem or issue that you are trying to address in the form of complete quantitative survey questions. Also, make sure to build an exhaustive list of response options to make sure your respondents select the correct response. If you miss adding important answer options, then the ones chosen by respondents may not be entirely true.

Types of Quantitative Research Questions With Examples

Quantitative research questions are generally used to answer the “who” and “what” of the research topic. For quantitative research to be effective, it is crucial that the respondents are able to answer your questions concisely and precisely. With that in mind, let’s look in greater detail at the three types of formats you can use when preparing quantitative market research questions.

1. Descriptive

Descriptive research questions are used to collect participants’ opinions about the variable that you want to quantify. It is the most effortless way to measure the particular variable (single or multiple variables) you are interested in on a large scale. Usually, descriptive research questions begin with “ how much,” “how often,” “what percentage,” “what proportion,” etc.

Examples of descriptive research questions include:

2. Comparative

Comparative research questions help you identify the difference between two or more groups based on one or more variables. In general, a comparative research question is used to quantify one variable; however, you can use two or more variables depending on your market research objectives.

Comparative research questions examples include:

3. Relationship-based

Relationship research questions are used to identify trends, causal relationships, or associations between two or more variables. It is not vital to distinguish between causal relationships, trends, or associations while using these types of questions. These questions begin with “What is the relationship” between independent and dependent variables, amongst or between two or more groups.

Relationship-based quantitative questions examples include:

Ready to Write Your Quantitative Research Questions?

So, there you have it. It was all about quantitative research question types and their examples. By now, you must have figured out a way to write quantitative research questions for your survey to collect actionable customer feedback.

Now, the only thing you need is a good survey maker tool, like ProProfs Survey Maker, that will glide your process of designing and conducting your surveys . You also get access to various survey question types, both qualitative and quantitative, that you can add to any kind of survey along with professionally-designed survey templates .

Jared Cornell

About the author

Jared cornell.

Jared is a customer support expert. He has been published in CrazyEgg , Foundr , and CXL . As a customer support executive at ProProfs, he has been instrumental in developing a complete customer support system that more than doubled customer satisfaction. You can connect and engage with Jared on Twitter , Facebook , and LinkedIn .

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How to structure quantitative research questions

There is no "one best way" to structure a quantitative research question. However, to create a well-structured quantitative research question, we recommend an approach that is based on four steps : (1) Choosing the type of quantitative research question you are trying to create (i.e., descriptive, comparative or relationship-based); (2) Identifying the different types of variables you are trying to measure, manipulate and/or control, as well as any groups you may be interested in; (3) Selecting the appropriate structure for the chosen type of quantitative research question, based on the variables and/or groups involved; and (4) Writing out the problem or issues you are trying to address in the form of a complete research question. In this article, we discuss each of these four steps , as well as providing examples for the three types of quantitative research question you may want to create: descriptive , comparative and relationship-based research questions .

  • STEP ONE: Choose the type of quantitative research question (i.e., descriptive, comparative or relationship) you are trying to create
  • STEP TWO: Identify the different types of variable you are trying to measure, manipulate and/or control, as well as any groups you may be interested in
  • STEP THREE: Select the appropriate structure for the chosen type of quantitative research question, based on the variables and/or groups involved
  • STEP FOUR: Write out the problem or issues you are trying to address in the form of a complete research question

STEP ONE Choose the type of quantitative research question (i.e., descriptive, comparative or relationship) you are trying to create

The type of quantitative research question that you use in your dissertation (i.e., descriptive , comparative and/or relationship-based ) needs to be reflected in the way that you write out the research question; that is, the word choice and phrasing that you use when constructing a research question tells the reader whether it is a descriptive, comparative or relationship-based research question. Therefore, in order to know how to structure your quantitative research question, you need to start by selecting the type of quantitative research question you are trying to create: descriptive, comparative and/or relationship-based.

STEP TWO Identify the different types of variable you are trying to measure, manipulate and/or control, as well as any groups you may be interested in

Whether you are trying to create a descriptive, comparative or relationship-based research question, you will need to identify the different types of variable that you are trying to measure , manipulate and/or control . If you are unfamiliar with the different types of variable that may be part of your study, the article, Types of variable , should get you up to speed. It explains the two main types of variables: categorical variables (i.e., nominal , dichotomous and ordinal variables) and continuous variables (i.e., interval and ratio variables). It also explains the difference between independent and dependent variables , which you need to understand to create quantitative research questions.

To provide a brief explanation; a variable is not only something that you measure , but also something that you can manipulate and control for. In most undergraduate and master's level dissertations, you are only likely to measure and manipulate variables. You are unlikely to carry out research that requires you to control for variables, although some supervisors will expect this additional level of complexity. If you plan to only create descriptive research questions , you may simply have a number of dependent variables that you need to measure. However, where you plan to create comparative and/or relationship-based research questions , you will deal with both dependent and independent variables . An independent variable (sometimes called an experimental or predictor variable ) is a variable that is being manipulated in an experiment in order to observe the effect this has on a dependent variable (sometimes called an outcome variable ). For example, if we were interested in investigating the relationship between gender and attitudes towards music piracy amongst adolescents , the independent variable would be gender and the dependent variable attitudes towards music piracy . This example also highlights the need to identify the group(s) you are interested in. In this example, the group of interest are adolescents .

Once you identifying the different types of variable you are trying to measure, manipulate and/or control, as well as any groups you may be interested in, it is possible to start thinking about the way that the three types of quantitative research question can be structured . This is discussed next.

STEP THREE Select the appropriate structure for the chosen type of quantitative research question, based on the variables and/or groups involved

The structure of the three types of quantitative research question differs, reflecting the goals of the question, the types of variables, and the number of variables and groups involved. By structure , we mean the components of a research question (i.e., the types of variables, groups of interest), the number of these different components (i.e., how many variables and groups are being investigated), and the order that these should be presented (e.g., independent variables before dependent variables). The appropriate structure for each of these quantitative research questions is set out below:

Structure of descriptive research questions

  • Structure of comparative research questions
  • Structure of relationship-based research questions

There are six steps required to construct a descriptive research question: (1) choose your starting phrase; (2) identify and name the dependent variable; (3) identify the group(s) you are interested in; (4) decide whether dependent variable or group(s) should be included first, last or in two parts; (5) include any words that provide greater context to your question; and (6) write out the descriptive research question. Each of these steps is discussed in turn:

Choose your starting phrase

Identify and name the dependent variable

Identify the group(s) you are interested in

Decide whether the dependent variable or group(s) should be included first, last or in two parts

Include any words that provide greater context to your question

Write out the descriptive research question

FIRST Choose your starting phrase

You can start descriptive research questions with any of the following phrases:

How many? How often? How frequently? How much? What percentage? What proportion? To what extent? What is? What are?

Some of these starting phrases are highlighted in blue text in the examples below:

How many calories do American men and women consume per day?

How often do British university students use Facebook each week?

What are the most important factors that influence the career choices of Australian university students?

What proportion of British male and female university students use the top 5 social networks?

What percentage of American men and women exceed their daily calorific allowance?

SECOND Identify and name the dependent variable

All descriptive research questions have a dependent variable. You need to identify what this is. However, how the dependent variable is written out in a research question and what you call it are often two different things. In the examples below, we have illustrated the name of the dependent variable and highlighted how it would be written out in the blue text .

The first two examples highlight that while the name of the dependent variable is the same, namely daily calorific intake , the way that this dependent variable is written out differs in each case.

THIRD Identify the group(s) you are interested in

All descriptive research questions have at least one group , but can have multiple groups . You need to identify this group(s). In the examples below, we have identified the group(s) in the green text .

What are the most important factors that influence the career choices of Australian university students ?

The examples illustrate the difference between the use of a single group (e.g., British university students ) and multiple groups (e.g., American men and women ).

FOURTH Decide whether the dependent variable or group(s) should be included first, last or in two parts

Sometimes it makes more sense for the dependent variable to appear before the group(s) you are interested in, but sometimes it is the opposite way around. The following examples illustrate this, with the group(s) in green text and the dependent variable in blue text :

Group 1st; dependent variable 2nd:

How often do British university students use Facebook each week ?

Dependent variable 1st; group 2nd:

Sometimes, the dependent variable needs to be broken into two parts around the group(s) you are interested in so that the research question flows. Again, the group(s) are in green text and the dependent variable is in blue text :

How many calories do American men and women consume per day ?

Of course, you could choose to restructure the question above so that you do not have to split the dependent variable into two parts. For example:

How many calories are consumed per day by American men and women ?

When deciding whether the dependent variable or group(s) should be included first or last, and whether the dependent variable should be broken into two parts, the main thing you need to think about is flow : Does the question flow? Is it easy to read?

FIFTH Include any words that provide greater context to your question

Sometimes the name of the dependent variable provides all the explanation we need to know what we are trying to measure. Take the following examples:

In the first example, the dependent variable is daily calorific intake (i.e., calories consumed per day). Clearly, this descriptive research question is asking us to measure the number of calories American men and women consume per day. In the second example, the dependent variable is Facebook usage per week. Again, the name of this dependent variable makes it easy for us to understand that we are trying to measure the often (i.e., how frequently; e.g., 16 times per week) British university students use Facebook.

However, sometimes a descriptive research question is not simply interested in measuring the dependent variable in its entirety, but a particular component of the dependent variable. Take the following examples in red text :

In the first example, the research question is not simply interested in the daily calorific intake of American men and women, but what percentage of these American men and women exceeded their daily calorific allowance. So the dependent variable is still daily calorific intake, but the research question aims to understand a particular component of that dependent variable (i.e., the percentage of American men and women exceeding the recommend daily calorific allowance). In the second example, the research question is not only interested in what the factors influencing career choices are, but which of these factors are the most important.

Therefore, when you think about constructing your descriptive research question, make sure you have included any words that provide greater context to your question.

SIXTH Write out the descriptive research question

Once you have these details ? (1) the starting phrase, (2) the name of the dependent variable, (3) the name of the group(s) you are interested in, and (4) any potential joining words ? you can write out the descriptive research question in full. The example descriptive research questions discussed above are written out in full below:

In the section that follows, the structure of comparative research questions is discussed.

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Organizing Your Social Sciences Research Paper

  • Quantitative Methods
  • Purpose of Guide
  • Design Flaws to Avoid
  • Independent and Dependent Variables
  • Glossary of Research Terms
  • Reading Research Effectively
  • Narrowing a Topic Idea
  • Broadening a Topic Idea
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  • Academic Writing Style
  • Choosing a Title
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  • Paragraph Development
  • Research Process Video Series
  • Executive Summary
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  • Background Information
  • The Research Problem/Question
  • Theoretical Framework
  • Citation Tracking
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  • Evaluating Sources
  • Primary Sources
  • Secondary Sources
  • Tiertiary Sources
  • Scholarly vs. Popular Publications
  • Qualitative Methods
  • Insiderness
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  • Limitations of the Study
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  • Writing Concisely
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  • Footnotes or Endnotes?
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  • Bibliography

Quantitative methods emphasize objective measurements and the statistical, mathematical, or numerical analysis of data collected through polls, questionnaires, and surveys, or by manipulating pre-existing statistical data using computational techniques . Quantitative research focuses on gathering numerical data and generalizing it across groups of people or to explain a particular phenomenon.

Babbie, Earl R. The Practice of Social Research . 12th ed. Belmont, CA: Wadsworth Cengage, 2010; Muijs, Daniel. Doing Quantitative Research in Education with SPSS . 2nd edition. London: SAGE Publications, 2010.

Need Help Locating Statistics?

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Statistics & Data Research Guide

Characteristics of Quantitative Research

Your goal in conducting quantitative research study is to determine the relationship between one thing [an independent variable] and another [a dependent or outcome variable] within a population. Quantitative research designs are either descriptive [subjects usually measured once] or experimental [subjects measured before and after a treatment]. A descriptive study establishes only associations between variables; an experimental study establishes causality.

Quantitative research deals in numbers, logic, and an objective stance. Quantitative research focuses on numeric and unchanging data and detailed, convergent reasoning rather than divergent reasoning [i.e., the generation of a variety of ideas about a research problem in a spontaneous, free-flowing manner].

Its main characteristics are :

  • The data is usually gathered using structured research instruments.
  • The results are based on larger sample sizes that are representative of the population.
  • The research study can usually be replicated or repeated, given its high reliability.
  • Researcher has a clearly defined research question to which objective answers are sought.
  • All aspects of the study are carefully designed before data is collected.
  • Data are in the form of numbers and statistics, often arranged in tables, charts, figures, or other non-textual forms.
  • Project can be used to generalize concepts more widely, predict future results, or investigate causal relationships.
  • Researcher uses tools, such as questionnaires or computer software, to collect numerical data.

The overarching aim of a quantitative research study is to classify features, count them, and construct statistical models in an attempt to explain what is observed.

  Things to keep in mind when reporting the results of a study using quantitative methods :

  • Explain the data collected and their statistical treatment as well as all relevant results in relation to the research problem you are investigating. Interpretation of results is not appropriate in this section.
  • Report unanticipated events that occurred during your data collection. Explain how the actual analysis differs from the planned analysis. Explain your handling of missing data and why any missing data does not undermine the validity of your analysis.
  • Explain the techniques you used to "clean" your data set.
  • Choose a minimally sufficient statistical procedure ; provide a rationale for its use and a reference for it. Specify any computer programs used.
  • Describe the assumptions for each procedure and the steps you took to ensure that they were not violated.
  • When using inferential statistics , provide the descriptive statistics, confidence intervals, and sample sizes for each variable as well as the value of the test statistic, its direction, the degrees of freedom, and the significance level [report the actual p value].
  • Avoid inferring causality , particularly in nonrandomized designs or without further experimentation.
  • Use tables to provide exact values ; use figures to convey global effects. Keep figures small in size; include graphic representations of confidence intervals whenever possible.
  • Always tell the reader what to look for in tables and figures .

NOTE:   When using pre-existing statistical data gathered and made available by anyone other than yourself [e.g., government agency], you still must report on the methods that were used to gather the data and describe any missing data that exists and, if there is any, provide a clear explanation why the missing data does not undermine the validity of your final analysis.

Babbie, Earl R. The Practice of Social Research . 12th ed. Belmont, CA: Wadsworth Cengage, 2010; Brians, Craig Leonard et al. Empirical Political Analysis: Quantitative and Qualitative Research Methods . 8th ed. Boston, MA: Longman, 2011; McNabb, David E. Research Methods in Public Administration and Nonprofit Management: Quantitative and Qualitative Approaches . 2nd ed. Armonk, NY: M.E. Sharpe, 2008; Quantitative Research Methods. Writing@CSU. Colorado State University; Singh, Kultar. Quantitative Social Research Methods . Los Angeles, CA: Sage, 2007.

Basic Research Design for Quantitative Studies

Before designing a quantitative research study, you must decide whether it will be descriptive or experimental because this will dictate how you gather, analyze, and interpret the results. A descriptive study is governed by the following rules: subjects are generally measured once; the intention is to only establish associations between variables; and, the study may include a sample population of hundreds or thousands of subjects to ensure that a valid estimate of a generalized relationship between variables has been obtained. An experimental design includes subjects measured before and after a particular treatment, the sample population may be very small and purposefully chosen, and it is intended to establish causality between variables. Introduction The introduction to a quantitative study is usually written in the present tense and from the third person point of view. It covers the following information:

  • Identifies the research problem -- as with any academic study, you must state clearly and concisely the research problem being investigated.
  • Reviews the literature -- review scholarship on the topic, synthesizing key themes and, if necessary, noting studies that have used similar methods of inquiry and analysis. Note where key gaps exist and how your study helps to fill these gaps or clarifies existing knowledge.
  • Describes the theoretical framework -- provide an outline of the theory or hypothesis underpinning your study. If necessary, define unfamiliar or complex terms, concepts, or ideas and provide the appropriate background information to place the research problem in proper context [e.g., historical, cultural, economic, etc.].

Methodology The methods section of a quantitative study should describe how each objective of your study will be achieved. Be sure to provide enough detail to enable the reader can make an informed assessment of the methods being used to obtain results associated with the research problem. The methods section should be presented in the past tense.

  • Study population and sampling -- where did the data come from; how robust is it; note where gaps exist or what was excluded. Note the procedures used for their selection;
  • Data collection – describe the tools and methods used to collect information and identify the variables being measured; describe the methods used to obtain the data; and, note if the data was pre-existing [i.e., government data] or you gathered it yourself. If you gathered it yourself, describe what type of instrument you used and why. Note that no data set is perfect--describe any limitations in methods of gathering data.
  • Data analysis -- describe the procedures for processing and analyzing the data. If appropriate, describe the specific instruments of analysis used to study each research objective, including mathematical techniques and the type of computer software used to manipulate the data.

Results The finding of your study should be written objectively and in a succinct and precise format. In quantitative studies, it is common to use graphs, tables, charts, and other non-textual elements to help the reader understand the data. Make sure that non-textual elements do not stand in isolation from the text but are being used to supplement the overall description of the results and to help clarify key points being made. Further information about how to effectively present data using charts and graphs can be found here .

  • Statistical analysis -- how did you analyze the data? What were the key findings from the data? The findings should be present in a logical, sequential order. Describe but do not interpret these trends or negative results; save that for the discussion section. The results should be presented in the past tense.

Discussion Discussions should be analytic, logical, and comprehensive. The discussion should meld together your findings in relation to those identified in the literature review, and placed within the context of the theoretical framework underpinning the study. The discussion should be presented in the present tense.

  • Interpretation of results -- reiterate the research problem being investigated and compare and contrast the findings with the research questions underlying the study. Did they affirm predicted outcomes or did the data refute it?
  • Description of trends, comparison of groups, or relationships among variables -- describe any trends that emerged from your analysis and explain all unanticipated and statistical insignificant findings.
  • Discussion of implications – what is the meaning of your results? Highlight key findings based on the overall results and note findings that you believe are important. How have the results helped fill gaps in understanding the research problem?
  • Limitations -- describe any limitations or unavoidable bias in your study and, if necessary, note why these limitations did not inhibit effective interpretation of the results.

Conclusion End your study by to summarizing the topic and provide a final comment and assessment of the study.

  • Summary of findings – synthesize the answers to your research questions. Do not report any statistical data here; just provide a narrative summary of the key findings and describe what was learned that you did not know before conducting the study.
  • Recommendations – if appropriate to the aim of the assignment, tie key findings with policy recommendations or actions to be taken in practice.
  • Future research – note the need for future research linked to your study’s limitations or to any remaining gaps in the literature that were not addressed in your study.

Black, Thomas R. Doing Quantitative Research in the Social Sciences: An Integrated Approach to Research Design, Measurement and Statistics . London: Sage, 1999; Gay,L. R. and Peter Airasain. Educational Research: Competencies for Analysis and Applications . 7th edition. Upper Saddle River, NJ: Merril Prentice Hall, 2003; Hector, Anestine. An Overview of Quantitative Research in Composition and TESOL . Department of English, Indiana University of Pennsylvania; Hopkins, Will G. “Quantitative Research Design.” Sportscience 4, 1 (2000); "A Strategy for Writing Up Research Results. The Structure, Format, Content, and Style of a Journal-Style Scientific Paper." Department of Biology. Bates College; Nenty, H. Johnson. "Writing a Quantitative Research Thesis." International Journal of Educational Science 1 (2009): 19-32; Ouyang, Ronghua (John). Basic Inquiry of Quantitative Research . Kennesaw State University.

Strengths of Using Quantitative Methods

Quantitative researchers try to recognize and isolate specific variables contained within the study framework, seek correlation, relationships and causality, and attempt to control the environment in which the data is collected to avoid the risk of variables, other than the one being studied, accounting for the relationships identified.

Among the specific strengths of using quantitative methods to study social science research problems:

  • Allows for a broader study, involving a greater number of subjects, and enhancing the generalization of the results;
  • Allows for greater objectivity and accuracy of results. Generally, quantitative methods are designed to provide summaries of data that support generalizations about the phenomenon under study. In order to accomplish this, quantitative research usually involves few variables and many cases, and employs prescribed procedures to ensure validity and reliability;
  • Applying well established standards means that the research can be replicated, and then analyzed and compared with similar studies;
  • You can summarize vast sources of information and make comparisons across categories and over time; and,
  • Personal bias can be avoided by keeping a 'distance' from participating subjects and using accepted computational techniques .

Babbie, Earl R. The Practice of Social Research . 12th ed. Belmont, CA: Wadsworth Cengage, 2010; Brians, Craig Leonard et al. Empirical Political Analysis: Quantitative and Qualitative Research Methods . 8th ed. Boston, MA: Longman, 2011; McNabb, David E. Research Methods in Public Administration and Nonprofit Management: Quantitative and Qualitative Approaches . 2nd ed. Armonk, NY: M.E. Sharpe, 2008; Singh, Kultar. Quantitative Social Research Methods . Los Angeles, CA: Sage, 2007.

Limitations of Using Quantitative Methods

Quantitative methods presume to have an objective approach to studying research problems, where data is controlled and measured, to address the accumulation of facts, and to determine the causes of behavior. As a consequence, the results of quantitative research may be statistically significant but are often humanly insignificant.

Some specific limitations associated with using quantitative methods to study research problems in the social sciences include:

  • Quantitative data is more efficient and able to test hypotheses, but may miss contextual detail;
  • Uses a static and rigid approach and so employs an inflexible process of discovery;
  • The development of standard questions by researchers can lead to "structural bias" and false representation, where the data actually reflects the view of the researcher instead of the participating subject;
  • Results provide less detail on behavior, attitudes, and motivation;
  • Researcher may collect a much narrower and sometimes superficial dataset;
  • Results are limited as they provide numerical descriptions rather than detailed narrative and generally provide less elaborate accounts of human perception;
  • The research is often carried out in an unnatural, artificial environment so that a level of control can be applied to the exercise. This level of control might not normally be in place in the real world thus yielding "laboratory results" as opposed to "real world results"; and,
  • Preset answers will not necessarily reflect how people really feel about a subject and, in some cases, might just be the closest match to the preconceived hypothesis.

Research Tip

Finding Examples of How to Apply Different Types of Research Methods

SAGE publications is a major publisher of studies about how to design and conduct research in the social and behavioral sciences. Their SAGE Research Methods Online and Cases database includes contents from books, articles, encyclopedias, handbooks, and videos covering social science research design and methods including the complete Little Green Book Series of Quantitative Applications in the Social Sciences and the Little Blue Book Series of Qualitative Research techniques. The database also includes case studies outlining the research methods used in real research projects. This is an excellent source for finding definitions of key terms and descriptions of research design and practice, techniques of data gathering, analysis, and reporting, and information about theories of research [e.g., grounded theory]. The database covers both qualitative and quantitative research methods as well as mixed methods approaches to conducting research.

SAGE Research Methods Online and Cases

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How to Write a Good Research Question (w/ Examples)

quantitative research essay questions

What is a Research Question?

A research question is the main question that your study sought or is seeking to answer. A clear research question guides your research paper or thesis and states exactly what you want to find out, giving your work a focus and objective. Learning  how to write a hypothesis or research question is the start to composing any thesis, dissertation, or research paper. It is also one of the most important sections of a research proposal . 

A good research question not only clarifies the writing in your study; it provides your readers with a clear focus and facilitates their understanding of your research topic, as well as outlining your study’s objectives. Before drafting the paper and receiving research paper editing (and usually before performing your study), you should write a concise statement of what this study intends to accomplish or reveal.

Research Question Writing Tips

Listed below are the important characteristics of a good research question:

A good research question should:

  • Be clear and provide specific information so readers can easily understand the purpose.
  • Be focused in its scope and narrow enough to be addressed in the space allowed by your paper
  • Be relevant and concise and express your main ideas in as few words as possible, like a hypothesis.
  • Be precise and complex enough that it does not simply answer a closed “yes or no” question, but requires an analysis of arguments and literature prior to its being considered acceptable. 
  • Be arguable or testable so that answers to the research question are open to scrutiny and specific questions and counterarguments.

Some of these characteristics might be difficult to understand in the form of a list. Let’s go into more detail about what a research question must do and look at some examples of research questions.

The research question should be specific and focused 

Research questions that are too broad are not suitable to be addressed in a single study. One reason for this can be if there are many factors or variables to consider. In addition, a sample data set that is too large or an experimental timeline that is too long may suggest that the research question is not focused enough.

A specific research question means that the collective data and observations come together to either confirm or deny the chosen hypothesis in a clear manner. If a research question is too vague, then the data might end up creating an alternate research problem or hypothesis that you haven’t addressed in your Introduction section .

The research question should be based on the literature 

An effective research question should be answerable and verifiable based on prior research because an effective scientific study must be placed in the context of a wider academic consensus. This means that conspiracy or fringe theories are not good research paper topics.

Instead, a good research question must extend, examine, and verify the context of your research field. It should fit naturally within the literature and be searchable by other research authors.

References to the literature can be in different citation styles and must be properly formatted according to the guidelines set forth by the publishing journal, university, or academic institution. This includes in-text citations as well as the Reference section . 

The research question should be realistic in time, scope, and budget

There are two main constraints to the research process: timeframe and budget.

A proper research question will include study or experimental procedures that can be executed within a feasible time frame, typically by a graduate doctoral or master’s student or lab technician. Research that requires future technology, expensive resources, or follow-up procedures is problematic.

A researcher’s budget is also a major constraint to performing timely research. Research at many large universities or institutions is publicly funded and is thus accountable to funding restrictions. 

The research question should be in-depth

Research papers, dissertations and theses , and academic journal articles are usually dozens if not hundreds of pages in length.

A good research question or thesis statement must be sufficiently complex to warrant such a length, as it must stand up to the scrutiny of peer review and be reproducible by other scientists and researchers.

Research Question Types

Qualitative and quantitative research are the two major types of research, and it is essential to develop research questions for each type of study. 

Quantitative Research Questions

Quantitative research questions are specific. A typical research question involves the population to be studied, dependent and independent variables, and the research design.

In addition, quantitative research questions connect the research question and the research design. In addition, it is not possible to answer these questions definitively with a “yes” or “no” response. For example, scientific fields such as biology, physics, and chemistry often deal with “states,” in which different quantities, amounts, or velocities drastically alter the relevance of the research.

As a consequence, quantitative research questions do not contain qualitative, categorical, or ordinal qualifiers such as “is,” “are,” “does,” or “does not.”

Categories of quantitative research questions

Qualitative research questions.

In quantitative research, research questions have the potential to relate to broad research areas as well as more specific areas of study. Qualitative research questions are less directional, more flexible, and adaptable compared with their quantitative counterparts. Thus, studies based on these questions tend to focus on “discovering,” “explaining,” “elucidating,” and “exploring.”

Categories of qualitative research questions

Quantitative and qualitative research question examples.

stacks of books in black and white; research question examples

Good and Bad Research Question Examples

Below are some good (and not-so-good) examples of research questions that researchers can use to guide them in crafting their own research questions.

Research Question Example 1

The first research question is too vague in both its independent and dependent variables. There is no specific information on what “exposure” means. Does this refer to comments, likes, engagement, or just how much time is spent on the social media platform?

Second, there is no useful information on what exactly “affected” means. Does the subject’s behavior change in some measurable way? Or does this term refer to another factor such as the user’s emotions?

Research Question Example 2

In this research question, the first example is too simple and not sufficiently complex, making it difficult to assess whether the study answered the question. The author could really only answer this question with a simple “yes” or “no.” Further, the presence of data would not help answer this question more deeply, which is a sure sign of a poorly constructed research topic.

The second research question is specific, complex, and empirically verifiable. One can measure program effectiveness based on metrics such as attendance or grades. Further, “bullying” is made into an empirical, quantitative measurement in the form of recorded disciplinary actions.

Steps for Writing a Research Question

Good research questions are relevant, focused, and meaningful. It can be difficult to come up with a good research question, but there are a few steps you can follow to make it a bit easier.

1. Start with an interesting and relevant topic

Choose a research topic that is interesting but also relevant and aligned with your own country’s culture or your university’s capabilities. Popular academic topics include healthcare and medical-related research. However, if you are attending an engineering school or humanities program, you should obviously choose a research question that pertains to your specific study and major.

Below is an embedded graph of the most popular research fields of study based on publication output according to region. As you can see, healthcare and the basic sciences receive the most funding and earn the highest number of publications. 

quantitative research essay questions

2. Do preliminary research  

You can begin doing preliminary research once you have chosen a research topic. Two objectives should be accomplished during this first phase of research. First, you should undertake a preliminary review of related literature to discover issues that scholars and peers are currently discussing. With this method, you show that you are informed about the latest developments in the field.

Secondly, identify knowledge gaps or limitations in your topic by conducting a preliminary literature review . It is possible to later use these gaps to focus your research question after a certain amount of fine-tuning.

3. Narrow your research to determine specific research questions

You can focus on a more specific area of study once you have a good handle on the topic you want to explore. Focusing on recent literature or knowledge gaps is one good option. 

By identifying study limitations in the literature and overlooked areas of study, an author can carve out a good research question. The same is true for choosing research questions that extend or complement existing literature.

4. Evaluate your research question

Make sure you evaluate the research question by asking the following questions:

Is my research question clear?

The resulting data and observations that your study produces should be clear. For quantitative studies, data must be empirical and measurable. For qualitative, the observations should be clearly delineable across categories.

Is my research question focused and specific?

A strong research question should be specific enough that your methodology or testing procedure produces an objective result, not one left to subjective interpretation. Open-ended research questions or those relating to general topics can create ambiguous connections between the results and the aims of the study. 

Is my research question sufficiently complex?

The result of your research should be consequential and substantial (and fall sufficiently within the context of your field) to warrant an academic study. Simply reinforcing or supporting a scientific consensus is superfluous and will likely not be well received by most journal editors.  

reverse triangle chart, how to write a research question

Editing Your Research Question

Your research question should be fully formulated well before you begin drafting your research paper. However, you can receive English paper editing and proofreading services at any point in the drafting process. Language editors with expertise in your academic field can assist you with the content and language in your Introduction section or other manuscript sections. And if you need further assistance or information regarding paper compositions, in the meantime, check out our academic resources , which provide dozens of articles and videos on a variety of academic writing and publication topics.

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  • What Is Quantitative Research? | Definition & Methods

What Is Quantitative Research? | Definition & Methods

Published on 4 April 2022 by Pritha Bhandari . Revised on 10 October 2022.

Quantitative research is the process of collecting and analysing numerical data. It can be used to find patterns and averages, make predictions, test causal relationships, and generalise results to wider populations.

Quantitative research is the opposite of qualitative research , which involves collecting and analysing non-numerical data (e.g. text, video, or audio).

Quantitative research is widely used in the natural and social sciences: biology, chemistry, psychology, economics, sociology, marketing, etc.

  • What is the demographic makeup of Singapore in 2020?
  • How has the average temperature changed globally over the last century?
  • Does environmental pollution affect the prevalence of honey bees?
  • Does working from home increase productivity for people with long commutes?

Table of contents

Quantitative research methods, quantitative data analysis, advantages of quantitative research, disadvantages of quantitative research, frequently asked questions about quantitative research.

You can use quantitative research methods for descriptive, correlational or experimental research.

  • In descriptive research , you simply seek an overall summary of your study variables.
  • In correlational research , you investigate relationships between your study variables.
  • In experimental research , you systematically examine whether there is a cause-and-effect relationship between variables.

Correlational and experimental research can both be used to formally test hypotheses , or predictions, using statistics. The results may be generalised to broader populations based on the sampling method used.

To collect quantitative data, you will often need to use operational definitions that translate abstract concepts (e.g., mood) into observable and quantifiable measures (e.g., self-ratings of feelings and energy levels).

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Once data is collected, you may need to process it before it can be analysed. For example, survey and test data may need to be transformed from words to numbers. Then, you can use statistical analysis to answer your research questions .

Descriptive statistics will give you a summary of your data and include measures of averages and variability. You can also use graphs, scatter plots and frequency tables to visualise your data and check for any trends or outliers.

Using inferential statistics , you can make predictions or generalisations based on your data. You can test your hypothesis or use your sample data to estimate the population parameter .

You can also assess the reliability and validity of your data collection methods to indicate how consistently and accurately your methods actually measured what you wanted them to.

Quantitative research is often used to standardise data collection and generalise findings . Strengths of this approach include:

  • Replication

Repeating the study is possible because of standardised data collection protocols and tangible definitions of abstract concepts.

  • Direct comparisons of results

The study can be reproduced in other cultural settings, times or with different groups of participants. Results can be compared statistically.

  • Large samples

Data from large samples can be processed and analysed using reliable and consistent procedures through quantitative data analysis.

  • Hypothesis testing

Using formalised and established hypothesis testing procedures means that you have to carefully consider and report your research variables, predictions, data collection and testing methods before coming to a conclusion.

Despite the benefits of quantitative research, it is sometimes inadequate in explaining complex research topics. Its limitations include:

  • Superficiality

Using precise and restrictive operational definitions may inadequately represent complex concepts. For example, the concept of mood may be represented with just a number in quantitative research, but explained with elaboration in qualitative research.

  • Narrow focus

Predetermined variables and measurement procedures can mean that you ignore other relevant observations.

  • Structural bias

Despite standardised procedures, structural biases can still affect quantitative research. Missing data , imprecise measurements or inappropriate sampling methods are biases that can lead to the wrong conclusions.

  • Lack of context

Quantitative research often uses unnatural settings like laboratories or fails to consider historical and cultural contexts that may affect data collection and results.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to test a hypothesis by systematically collecting and analysing data, while qualitative methods allow you to explore ideas and experiences in depth.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organisations.

Operationalisation means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioural avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalise the variables that you want to measure.

Reliability and validity are both about how well a method measures something:

  • Reliability refers to the  consistency of a measure (whether the results can be reproduced under the same conditions).
  • Validity   refers to the  accuracy of a measure (whether the results really do represent what they are supposed to measure).

If you are doing experimental research , you also have to consider the internal and external validity of your experiment.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

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Writing Studio

Formulating your research question (rq).

In an effort to make our handouts more accessible, we have begun converting our PDF handouts to web pages. Download this page as a PDF: Formulating Your Research Question Return to Writing Studio Handouts

In a research paper, the emphasis is on generating a unique question and then synthesizing diverse sources into a coherent essay that supports your argument about the topic. In other words, you integrate information from publications with your own thoughts in order to formulate an argument. Your topic is your starting place: from here, you will develop an engaging research question. Merely presenting a topic in the form of a question does not transform it into a good research question.

Research Topic Versus Research Question Examples

1. broad topic versus narrow question, 1a. broad topic.

“What forces affect race relations in America?”

1b. NARROWER QUESTION

“How do corporate hiring practices affect race relations in Nashville?”

The question “What is the percentage of racial minorities holding management positions in corporate offices in Nashville?” is much too specific and would yield, at best, a statistic that could become part of a larger argument.

2. Neutral Topic Versus Argumentative Question

2a. neutral topic.

“How does KFC market its low-fat food offerings?”

2b. Argumentative question

“Does KFC put more money into marketing its high-fat food offerings than its lower-fat ones?”

The latter question is somewhat better, since it may lead you to take a stance or formulate an argument about consumer awareness or benefit.

3. Objective Topic Versus Subjective Question

Objective subjects are factual and do not have sides to be argued. Subjective subjects are those about which you can take a side.

3a. Objective topic

“How much time do youth between the ages of 10 and 15 spend playing video games?”

3b. Subjective Question

“What are the effects of video-gaming on the attention spans of youth between the ages of 10 and 15?”

The first question is likely to lead to some data, though not necessarily to an argument or issue. The second question is somewhat better, since it might lead you to formulate an argument for or against time spent playing video games.

4. Open-Ended Topic Versus Direct Question

4a. open-ended topic.

“Does the author of this text use allusion?”

4b. Direct question (gives direction to research)

“Does the ironic use of allusion in this text reveal anything about the author’s unwillingness to divulge his political commitments?”

The second question gives focus by putting the use of allusion into the specific context of a question about the author’s political commitments and perhaps also about the circumstances under which the text was produced.

Research Question (RQ) Checklist

  • Is my RQ something that I am curious about and that others might care about? Does it present an issue on which I can take a stand?
  • Does my RQ put a new spin on an old issue, or does it try to solve a problem?
  • Is my RQ too broad, too narrow, or OK?
  • within the time frame of the assignment?
  • given the resources available at my location?
  • Is my RQ measurable? What type of information do I need? Can I find actual data to support or contradict a position?
  • What sources will have the type of information that I need to answer my RQ (journals, books, internet resources, government documents, interviews with people)?

Final Thoughts

The answer to a good research question will often be the THESIS of your research paper! And the results of your research may not always be what you expected them to be. Not only is this ok, it can be an indication that you are doing careful work!

Adapted from an online tutorial at Empire State College: http://www.esc.edu/htmlpages/writerold/menus.htm#develop (broken link)

Last revised: November 2022 | Adapted for web delivery: November 2022

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How to Write a Research Question: Types and Examples 

research quetsion

The first step in any research project is framing the research question. It can be considered the core of any systematic investigation as the research outcomes are tied to asking the right questions. Thus, this primary interrogation point sets the pace for your research as it helps collect relevant and insightful information that ultimately influences your work.   

Typically, the research question guides the stages of inquiry, analysis, and reporting. Depending on the use of quantifiable or quantitative data, research questions are broadly categorized into quantitative or qualitative research questions. Both types of research questions can be used independently or together, considering the overall focus and objectives of your research.  

What is a research question?

A research question is a clear, focused, concise, and arguable question on which your research and writing are centered. 1 It states various aspects of the study, including the population and variables to be studied and the problem the study addresses. These questions also set the boundaries of the study, ensuring cohesion. 

Designing the research question is a dynamic process where the researcher can change or refine the research question as they review related literature and develop a framework for the study. Depending on the scale of your research, the study can include single or multiple research questions. 

A good research question has the following features: 

  • It is relevant to the chosen field of study. 
  • The question posed is arguable and open for debate, requiring synthesizing and analysis of ideas. 
  • It is focused and concisely framed. 
  • A feasible solution is possible within the given practical constraint and timeframe. 

A poorly formulated research question poses several risks. 1   

  • Researchers can adopt an erroneous design. 
  • It can create confusion and hinder the thought process, including developing a clear protocol.  
  • It can jeopardize publication efforts.  
  • It causes difficulty in determining the relevance of the study findings.  
  • It causes difficulty in whether the study fulfils the inclusion criteria for systematic review and meta-analysis. This creates challenges in determining whether additional studies or data collection is needed to answer the question.  
  • Readers may fail to understand the objective of the study. This reduces the likelihood of the study being cited by others. 

Now that you know “What is a research question?”, let’s look at the different types of research questions. 

Types of research questions

Depending on the type of research to be done, research questions can be classified broadly into quantitative, qualitative, or mixed-methods studies. Knowing the type of research helps determine the best type of research question that reflects the direction and epistemological underpinnings of your research. 

The structure and wording of quantitative 2 and qualitative research 3 questions differ significantly. The quantitative study looks at causal relationships, whereas the qualitative study aims at exploring a phenomenon. 

  • Quantitative research questions:  
  • Seeks to investigate social, familial, or educational experiences or processes in a particular context and/or location.  
  • Answers ‘how,’ ‘what,’ or ‘why’ questions. 
  • Investigates connections, relations, or comparisons between independent and dependent variables. 

Quantitative research questions can be further categorized into descriptive, comparative, and relationship, as explained in the Table below. 

  • Qualitative research questions  

Qualitative research questions are adaptable, non-directional, and more flexible. It concerns broad areas of research or more specific areas of study to discover, explain, or explore a phenomenon. These are further classified as follows: 

  • Mixed-methods studies  

Mixed-methods studies use both quantitative and qualitative research questions to answer your research question. Mixed methods provide a complete picture than standalone quantitative or qualitative research, as it integrates the benefits of both methods. Mixed methods research is often used in multidisciplinary settings and complex situational or societal research, especially in the behavioral, health, and social science fields. 

What makes a good research question

A good research question should be clear and focused to guide your research. It should synthesize multiple sources to present your unique argument, and should ideally be something that you are interested in. But avoid questions that can be answered in a few factual statements. The following are the main attributes of a good research question. 

  • Specific: The research question should not be a fishing expedition performed in the hopes that some new information will be found that will benefit the researcher. The central research question should work with your research problem to keep your work focused. If using multiple questions, they should all tie back to the central aim. 
  • Measurable: The research question must be answerable using quantitative and/or qualitative data or from scholarly sources to develop your research question. If such data is impossible to access, it is better to rethink your question. 
  • Attainable: Ensure you have enough time and resources to do all research required to answer your question. If it seems you will not be able to gain access to the data you need, consider narrowing down your question to be more specific. 
  • You have the expertise 
  • You have the equipment and resources 
  • Realistic: Developing your research question should be based on initial reading about your topic. It should focus on addressing a problem or gap in the existing knowledge in your field or discipline. 
  • Based on some sort of rational physics 
  • Can be done in a reasonable time frame 
  • Timely: The research question should contribute to an existing and current debate in your field or in society at large. It should produce knowledge that future researchers or practitioners can later build on. 
  • Novel 
  • Based on current technologies. 
  • Important to answer current problems or concerns. 
  • Lead to new directions. 
  • Important: Your question should have some aspect of originality. Incremental research is as important as exploring disruptive technologies. For example, you can focus on a specific location or explore a new angle. 
  • Meaningful whether the answer is “Yes” or “No.” Closed-ended, yes/no questions are too simple to work as good research questions. Such questions do not provide enough scope for robust investigation and discussion. A good research question requires original data, synthesis of multiple sources, and original interpretation and argumentation before providing an answer. 

Steps for developing a good research question

The importance of research questions cannot be understated. When drafting a research question, use the following frameworks to guide the components of your question to ease the process. 4  

  • Determine the requirements: Before constructing a good research question, set your research requirements. What is the purpose? Is it descriptive, comparative, or explorative research? Determining the research aim will help you choose the most appropriate topic and word your question appropriately. 
  • Select a broad research topic: Identify a broader subject area of interest that requires investigation. Techniques such as brainstorming or concept mapping can help identify relevant connections and themes within a broad research topic. For example, how to learn and help students learn. 
  • Perform preliminary investigation: Preliminary research is needed to obtain up-to-date and relevant knowledge on your topic. It also helps identify issues currently being discussed from which information gaps can be identified. 
  • Narrow your focus: Narrow the scope and focus of your research to a specific niche. This involves focusing on gaps in existing knowledge or recent literature or extending or complementing the findings of existing literature. Another approach involves constructing strong research questions that challenge your views or knowledge of the area of study (Example: Is learning consistent with the existing learning theory and research). 
  • Identify the research problem: Once the research question has been framed, one should evaluate it. This is to realize the importance of the research questions and if there is a need for more revising (Example: How do your beliefs on learning theory and research impact your instructional practices). 

How to write a research question

Those struggling to understand how to write a research question, these simple steps can help you simplify the process of writing a research question. 

Sample Research Questions

The following are some bad and good research question examples 

  • Example 1 
  • Example 2 

References:  

  • Thabane, L., Thomas, T., Ye, C., & Paul, J. (2009). Posing the research question: not so simple.  Canadian Journal of Anesthesia/Journal canadien d’anesthésie ,  56 (1), 71-79. 
  • Rutberg, S., & Bouikidis, C. D. (2018). Focusing on the fundamentals: A simplistic differentiation between qualitative and quantitative research.  Nephrology Nursing Journal ,  45 (2), 209-213. 
  • Kyngäs, H. (2020). Qualitative research and content analysis.  The application of content analysis in nursing science research , 3-11. 
  • Mattick, K., Johnston, J., & de la Croix, A. (2018). How to… write a good research question.  The clinical teacher ,  15 (2), 104-108. 
  • Fandino, W. (2019). Formulating a good research question: Pearls and pitfalls.  Indian Journal of Anaesthesia ,  63 (8), 611. 
  • Richardson, W. S., Wilson, M. C., Nishikawa, J., & Hayward, R. S. (1995). The well-built clinical question: a key to evidence-based decisions.  ACP journal club ,  123 (3), A12-A13 

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  • What is a Thesis Statement and How to Write It (with Examples) 
  • How to Write a Good Humanities Research Paper
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4.3 Quantitative research questions

Learning objectives.

  • Describe how research questions for exploratory, descriptive, and explanatory quantitative questions differ and how to phrase them
  • Identify the differences between and provide examples of strong and weak explanatory research questions

Quantitative descriptive questions

The type of research you are conducting will impact the research question that you ask. Probably the easiest questions to think of are quantitative descriptive questions. For example, “What is the average student debt load of MSW students?” is a descriptive question—and an important one. We aren’t trying to build a causal relationship here. We’re simply trying to describe how much debt MSW students carry. Quantitative descriptive questions like this one are helpful in social work practice as part of community scans, in which human service agencies survey the various needs of the community they serve. If the scan reveals that the community requires more services related to housing, child care, or day treatment for people with disabilities, a nonprofit office can use the community scan to create new programs that meet a defined community need.

an illuminated street sign that reads "ask"

Quantitative descriptive questions will often ask for percentage, count the number of instances of a phenomenon, or determine an average. Descriptive questions may only include one variable, such as ours about debt load, or they may include multiple variables. Because these are descriptive questions, we cannot investigate causal relationships between variables. To do that, we need to use a quantitative explanatory question.

Quantitative explanatory questions

Most studies you read in the academic literature will be quantitative and explanatory. Why is that? Explanatory research tries to build something called nomothetic causal explanations.Matthew DeCarlo says “com[ing]up with a broad, sweeping explanation that is universally true for all people” is the hallmark of nomothetic causal relationships (DeCarlo, 2018, chapter 7.2, para 5 ). They are generalizable across space and time, so they are applicable to a wide audience. The editorial board of a journal wants to make sure their content will be useful to as many people as possible, so it’s not surprising that quantitative research dominates the academic literature.

Structurally, quantitative explanatory questions must contain an independent variable and dependent variable. Questions should ask about the relation between these variables. A standard format for an explanatory quantitative research question is: “What is the relation between [independent variable] and [dependent variable] for [target population]?” You should play with the wording for your research question, revising it as you see fit. The goal is to make the research question reflect what you really want to know in your study.

Let’s take a look at a few more examples of possible research questions and consider the relative strengths and weaknesses of each. Table 4.1 does just that. While reading the table, keep in mind that it only includes some of the most relevant strengths and weaknesses of each question. Certainly each question may have additional strengths and weaknesses not noted in the table.

Making it more specific

A good research question should also be specific and clear about the concepts it addresses. A group of students investigating gender and household tasks knows what they mean by “household tasks.” You likely also have an impression of what “household tasks” means. But are your definition and the students’ definition the same? A participant in their study may think that managing finances and performing home maintenance are household tasks, but the researcher may be interested in other tasks like childcare or cleaning. The only way to ensure your study stays focused and clear is to be specific about what you mean by a concept. The student in our example could pick a specific household task that was interesting to them or that the literature indicated was important—for example, childcare. Or, the student could have a broader view of household tasks, one that encompasses childcare, food preparation, financial management, home repair, and care for relatives. Any option is probably okay, as long as the researchers are clear on what they mean by “household tasks.”

Table 4.2 contains some “watch words” that indicate you may need to be more specific about the concepts in your research question.

It can be challenging in social work research to be this specific, particularly when you are just starting out your investigation of the topic. If you’ve only read one or two articles on the topic, it can be hard to know what you are interested in studying. Broad questions like “What are the causes of chronic homelessness, and what can be done to prevent it?” are common at the beginning stages of a research project. However, social work research demands that you examine the literature on the topic and refine your question over time to be more specific and clear before you begin your study. Perhaps you want to study the effect of a specific anti-homelessness program that you found in the literature. Maybe there is a particular model to fighting homelessness, like Housing First or transitional housing that you want to investigate further. You may want to focus on a potential cause of homelessness such as LGBTQ discrimination that you find interesting or relevant to your practice. As you can see, the possibilities for making your question more specific are almost infinite.

Quantitative exploratory questions

In exploratory research, the researcher doesn’t quite know the lay of the land yet. If someone is proposing to conduct an exploratory quantitative project, the watch words highlighted in Table 4.2 are not problematic at all. In fact, questions such as “What factors influence the removal of children in child welfare cases?” are good because they will explore a variety of factors or causes. In this question, the independent variable is less clearly written, but the dependent variable, family preservation outcomes, is quite clearly written. The inverse can also be true. If we were to ask, “What outcomes are associated with family preservation services in child welfare?”, we would have a clear independent variable, family preservation services, but an unclear dependent variable, outcomes. Because we are only conducting exploratory research on a topic, we may not have an idea of what concepts may comprise our “outcomes” or “factors.” Only after interacting with our participants will we be able to understand which concepts are important.

Key Takeaways

  • Quantitative descriptive questions are helpful for community scans but cannot investigate causal relationships between variables.
  • Quantitative explanatory questions must include an independent and dependent variable.

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Guidebook for Social Work Literature Reviews and Research Questions Copyright © 2020 by Rebecca Mauldin and Matthew DeCarlo is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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50+ Interesting Quantitative Research Topics

Home / Blog / 50+ Interesting Quantitative Research Topics

50+ Interesting Quantitative Research Topics

Introduction

Quantitative research questions can be tricky at times. Student needs to choose the type of question he/she would like to answer or work on. Even though one may find picking a quantitative research paper topic easy, things might turn out to be overly complicated for an individual who isn’t aware of the technicalities.

 Now that you too are grappling with the intricacy of choosing an ideal quantitative research paper topic, consider reading through this blog. I will be discussing the various technicalities that can be implemented in order to choose and structure a quantitative research question. What’s more?  I will be sharing a list of 50+ unique quantitative research topics for you.

HOW TO CHOOSE QUANTITATIVE RESEARCH TOPICS

Brought in one of its academic journals by the British Library, quantitative research questions are generally used in order to set the scene for industry reports or an entire study. There are basically three common types of quantitative research questions you will come across. Let’s take a look at them.

essay

Types of Quantitative Research Questions

Now that you are aware of the 3 crucial types of quantitative research questions, it’s time to know how to select an ideal topic or a question in different situations. Here’s a smart chart illustrating the same. Take a look.

table

 How to Choose a Quantitative Research Question

I am going to share further details with an explicitly discussed theoretical insight into the context of choosing an ideal quantitative research question. Take note:

Step 1: Choose the research topic 

Remember, your research question will represent the type of quantitative research you will use in your dissertation.  So, you should always consider choosing the type of research question quite carefully. It can be descriptive, comparative or relationship-based. If you already have a couple of plants and unique ideas in your head, figure out if they are rational and relevant in nature.

 Once you are done deciding the same, figure out the type of research question you can form using that particular idea. It goes without saying; you are required to come up with different perspectives and styles for each of the aforementioned research question types.

Step 2: Identify the variables 

It doesn’t matter whether you are working on a relationship-based, comparative or descriptive research question.  You should consider identifying the different aspects you will try to control, manipulate or measure.

There are primarily two types of variables; categorical variables and continuous variables. In addition, you need to develop an understanding of the fundamentals of dependent variables and independent variables. In case you are planning to structure a research paper based on descriptive questions, then you need to measure a number of dependent variables. On the other hand, working on a comparative or relationship-based research question will require you to deal with independent and dependent variables as well. Once you are done indentifying the individual variables associated with different types of research questions, you need to plan a perfect structure.

Step 3: Choose the appropriate structure for different types of questions 

The structure is different for each of the three types of research questions. Take a look.

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Structure of Descriptive Research Questions

data of essay

Structure of Comparative Research Questions

stucture

Structure of Relationship-based Research Questions

Step 4:  Jot down the issues you would address 

Now that you are done structuring the questions for the individual research types, it’s time to jot down the issues you would like to address. You have to be more attentive and flawless. Remember, you should consider highlighting each of the issues and addressing the same in simple languages.

The idea is to frame readable quantitative research papers. It should not appear to be convoluted in nature and must solve the purpose of establishing rational perspectives. In addition, it should also maintain a unified structure throughout the paper.

Moving on to the next section, here is a set of 50+ unique and crucial quantitative research questions for you to explore.

  • The relationship between crime statistics and immigration.
  • The impact of education on obesity.
  • The relationship between electoral results and consumer confidence.
  • What are the issues faced by Uber? What can be done in order to solve such issues?
  • The link between competitive risk assignment and estimated target market.
  • The impact of net neutrality and what could possibly happen in the future.
  • The strategy that saved IBM from going insolvent.
  • The aspect of gambling from the perspective of psychology.
  • How Magna Carta changed England?
  • Associated risks of confidential data storage and detection.
  • How is workplace diversity helping organizations become more productive?
  • The advantages and disadvantages of outsourcing services.
  • Is franchising really beneficial for businesses in and around the United Kingdom?
  • The advantages and disadvantages of Social Security Reform.
  • The pros and cons of social education in groups.
  • Is liberalism an ideal solution?
  • Are loyalty programs the most essential component of marketing?
  • The rise and impact of social media in marketing.
  • The advantages and disadvantages of setting up start-ups in the United Kingdom.
  • Benefits of Black Friday sales.
  • The impact of market segmentation in the United Kingdom.
  • The fundamentals and vision of Kellogg on Marketing.
  • The definition of viability and its link with the scientific evidence for abortion.
  • The role and impact of IT infrastructure Usage in the Healthcare industry.
  • Quantitative analysis of the marketing strategies followed by different automobile companies in and around the United Kingdom.
  • The effect of public relations in corporate organisations.
  • The link between online blogs, press releases and business development.
  • Using social insights for better marketing ROIs.
  • The impact of the recession on promotional activities related to marketing assignment help
  • Will society be better without the inclusion of organised religion?
  • The implementation and impact of brain chips.
  • The effect of relationship marketing in various UK-based corporate organisations.
  • Different strategies to measure consumer satisfaction.
  • The ethics and fundamentals of pharmaceutical marketing.
  • The role and impact of religious iconography in a nation.
  • How bioterrorism can bring in the negative impact on the environment around us?
  • The role and impact of nuclear energy in today’s world.
  • The link between academic achievement and economic status.
  • The relationship between retirement and debt accumulation.
  • Comparing the strategic display of a product of different brands.
  • The link between fiscal decentralization and innovation.
  • The relationship between cognitive development and child nutrition.
  • The impact of solar electricity on the wholesale energy market.
  • The link between micro financial participation and expectations.
  • Quantitative analysis of the number of homeless people in the United Kingdom.
  • What is the difference between the daily calorific intake of British men and women?
  • Should marijuana be legalised worldwide?
  • The relationship between economic growth and urbanisation.
  • What percent of Great Britain residents are falling short of their daily dose of vitamins?
  • What percent of Great Britain residents owns pets?
  • The advantages and disadvantages of online banking.
  • Strategies to calculate the sample size of G Power Analysis.
  • Evaluating nurse’s knowledge of dysphagia by quantitative research.
  • Is international civil society a contemporary form of neo-colonialism?
  • The role of quarantine in current epidemiological practices.
  • How can be creativity measured in online advertising?

Take some time out to evaluate each of the topics and select the one that appears to be interesting. Refer to the suggestions as well, and I hope you will be able to come up with a well-knit quantitative research paper this semester.

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Research Method

Home » 500+ Quantitative Research Titles and Topics

500+ Quantitative Research Titles and Topics

Table of Contents

Quantitative Research Topics

Quantitative research involves collecting and analyzing numerical data to identify patterns, trends, and relationships among variables. This method is widely used in social sciences, psychology , economics , and other fields where researchers aim to understand human behavior and phenomena through statistical analysis. If you are looking for a quantitative research topic, there are numerous areas to explore, from analyzing data on a specific population to studying the effects of a particular intervention or treatment. In this post, we will provide some ideas for quantitative research topics that may inspire you and help you narrow down your interests.

Quantitative Research Titles

Quantitative Research Titles are as follows:

Business and Economics

  • “Statistical Analysis of Supply Chain Disruptions on Retail Sales”
  • “Quantitative Examination of Consumer Loyalty Programs in the Fast Food Industry”
  • “Predicting Stock Market Trends Using Machine Learning Algorithms”
  • “Influence of Workplace Environment on Employee Productivity: A Quantitative Study”
  • “Impact of Economic Policies on Small Businesses: A Regression Analysis”
  • “Customer Satisfaction and Profit Margins: A Quantitative Correlation Study”
  • “Analyzing the Role of Marketing in Brand Recognition: A Statistical Overview”
  • “Quantitative Effects of Corporate Social Responsibility on Consumer Trust”
  • “Price Elasticity of Demand for Luxury Goods: A Case Study”
  • “The Relationship Between Fiscal Policy and Inflation Rates: A Time-Series Analysis”
  • “Factors Influencing E-commerce Conversion Rates: A Quantitative Exploration”
  • “Examining the Correlation Between Interest Rates and Consumer Spending”
  • “Standardized Testing and Academic Performance: A Quantitative Evaluation”
  • “Teaching Strategies and Student Learning Outcomes in Secondary Schools: A Quantitative Study”
  • “The Relationship Between Extracurricular Activities and Academic Success”
  • “Influence of Parental Involvement on Children’s Educational Achievements”
  • “Digital Literacy in Primary Schools: A Quantitative Assessment”
  • “Learning Outcomes in Blended vs. Traditional Classrooms: A Comparative Analysis”
  • “Correlation Between Teacher Experience and Student Success Rates”
  • “Analyzing the Impact of Classroom Technology on Reading Comprehension”
  • “Gender Differences in STEM Fields: A Quantitative Analysis of Enrollment Data”
  • “The Relationship Between Homework Load and Academic Burnout”
  • “Assessment of Special Education Programs in Public Schools”
  • “Role of Peer Tutoring in Improving Academic Performance: A Quantitative Study”

Medicine and Health Sciences

  • “The Impact of Sleep Duration on Cardiovascular Health: A Cross-sectional Study”
  • “Analyzing the Efficacy of Various Antidepressants: A Meta-Analysis”
  • “Patient Satisfaction in Telehealth Services: A Quantitative Assessment”
  • “Dietary Habits and Incidence of Heart Disease: A Quantitative Review”
  • “Correlations Between Stress Levels and Immune System Functioning”
  • “Smoking and Lung Function: A Quantitative Analysis”
  • “Influence of Physical Activity on Mental Health in Older Adults”
  • “Antibiotic Resistance Patterns in Community Hospitals: A Quantitative Study”
  • “The Efficacy of Vaccination Programs in Controlling Disease Spread: A Time-Series Analysis”
  • “Role of Social Determinants in Health Outcomes: A Quantitative Exploration”
  • “Impact of Hospital Design on Patient Recovery Rates”
  • “Quantitative Analysis of Dietary Choices and Obesity Rates in Children”

Social Sciences

  • “Examining Social Inequality through Wage Distribution: A Quantitative Study”
  • “Impact of Parental Divorce on Child Development: A Longitudinal Study”
  • “Social Media and its Effect on Political Polarization: A Quantitative Analysis”
  • “The Relationship Between Religion and Social Attitudes: A Statistical Overview”
  • “Influence of Socioeconomic Status on Educational Achievement”
  • “Quantifying the Effects of Community Programs on Crime Reduction”
  • “Public Opinion and Immigration Policies: A Quantitative Exploration”
  • “Analyzing the Gender Representation in Political Offices: A Quantitative Study”
  • “Impact of Mass Media on Public Opinion: A Regression Analysis”
  • “Influence of Urban Design on Social Interactions in Communities”
  • “The Role of Social Support in Mental Health Outcomes: A Quantitative Analysis”
  • “Examining the Relationship Between Substance Abuse and Employment Status”

Engineering and Technology

  • “Performance Evaluation of Different Machine Learning Algorithms in Autonomous Vehicles”
  • “Material Science: A Quantitative Analysis of Stress-Strain Properties in Various Alloys”
  • “Impacts of Data Center Cooling Solutions on Energy Consumption”
  • “Analyzing the Reliability of Renewable Energy Sources in Grid Management”
  • “Optimization of 5G Network Performance: A Quantitative Assessment”
  • “Quantifying the Effects of Aerodynamics on Fuel Efficiency in Commercial Airplanes”
  • “The Relationship Between Software Complexity and Bug Frequency”
  • “Machine Learning in Predictive Maintenance: A Quantitative Analysis”
  • “Wearable Technologies and their Impact on Healthcare Monitoring”
  • “Quantitative Assessment of Cybersecurity Measures in Financial Institutions”
  • “Analysis of Noise Pollution from Urban Transportation Systems”
  • “The Influence of Architectural Design on Energy Efficiency in Buildings”

Quantitative Research Topics

Quantitative Research Topics are as follows:

  • The effects of social media on self-esteem among teenagers.
  • A comparative study of academic achievement among students of single-sex and co-educational schools.
  • The impact of gender on leadership styles in the workplace.
  • The correlation between parental involvement and academic performance of students.
  • The effect of mindfulness meditation on stress levels in college students.
  • The relationship between employee motivation and job satisfaction.
  • The effectiveness of online learning compared to traditional classroom learning.
  • The correlation between sleep duration and academic performance among college students.
  • The impact of exercise on mental health among adults.
  • The relationship between social support and psychological well-being among cancer patients.
  • The effect of caffeine consumption on sleep quality.
  • A comparative study of the effectiveness of cognitive-behavioral therapy and pharmacotherapy in treating depression.
  • The relationship between physical attractiveness and job opportunities.
  • The correlation between smartphone addiction and academic performance among high school students.
  • The impact of music on memory recall among adults.
  • The effectiveness of parental control software in limiting children’s online activity.
  • The relationship between social media use and body image dissatisfaction among young adults.
  • The correlation between academic achievement and parental involvement among minority students.
  • The impact of early childhood education on academic performance in later years.
  • The effectiveness of employee training and development programs in improving organizational performance.
  • The relationship between socioeconomic status and access to healthcare services.
  • The correlation between social support and academic achievement among college students.
  • The impact of technology on communication skills among children.
  • The effectiveness of mindfulness-based stress reduction programs in reducing symptoms of anxiety and depression.
  • The relationship between employee turnover and organizational culture.
  • The correlation between job satisfaction and employee engagement.
  • The impact of video game violence on aggressive behavior among children.
  • The effectiveness of nutritional education in promoting healthy eating habits among adolescents.
  • The relationship between bullying and academic performance among middle school students.
  • The correlation between teacher expectations and student achievement.
  • The impact of gender stereotypes on career choices among high school students.
  • The effectiveness of anger management programs in reducing violent behavior.
  • The relationship between social support and recovery from substance abuse.
  • The correlation between parent-child communication and adolescent drug use.
  • The impact of technology on family relationships.
  • The effectiveness of smoking cessation programs in promoting long-term abstinence.
  • The relationship between personality traits and academic achievement.
  • The correlation between stress and job performance among healthcare professionals.
  • The impact of online privacy concerns on social media use.
  • The effectiveness of cognitive-behavioral therapy in treating anxiety disorders.
  • The relationship between teacher feedback and student motivation.
  • The correlation between physical activity and academic performance among elementary school students.
  • The impact of parental divorce on academic achievement among children.
  • The effectiveness of diversity training in improving workplace relationships.
  • The relationship between childhood trauma and adult mental health.
  • The correlation between parental involvement and substance abuse among adolescents.
  • The impact of social media use on romantic relationships among young adults.
  • The effectiveness of assertiveness training in improving communication skills.
  • The relationship between parental expectations and academic achievement among high school students.
  • The correlation between sleep quality and mood among adults.
  • The impact of video game addiction on academic performance among college students.
  • The effectiveness of group therapy in treating eating disorders.
  • The relationship between job stress and job performance among teachers.
  • The correlation between mindfulness and emotional regulation.
  • The impact of social media use on self-esteem among college students.
  • The effectiveness of parent-teacher communication in promoting academic achievement among elementary school students.
  • The impact of renewable energy policies on carbon emissions
  • The relationship between employee motivation and job performance
  • The effectiveness of psychotherapy in treating eating disorders
  • The correlation between physical activity and cognitive function in older adults
  • The effect of childhood poverty on adult health outcomes
  • The impact of urbanization on biodiversity conservation
  • The relationship between work-life balance and employee job satisfaction
  • The effectiveness of eye movement desensitization and reprocessing (EMDR) in treating trauma
  • The correlation between parenting styles and child behavior
  • The effect of social media on political polarization
  • The impact of foreign aid on economic development
  • The relationship between workplace diversity and organizational performance
  • The effectiveness of dialectical behavior therapy in treating borderline personality disorder
  • The correlation between childhood abuse and adult mental health outcomes
  • The effect of sleep deprivation on cognitive function
  • The impact of trade policies on international trade and economic growth
  • The relationship between employee engagement and organizational commitment
  • The effectiveness of cognitive therapy in treating postpartum depression
  • The correlation between family meals and child obesity rates
  • The effect of parental involvement in sports on child athletic performance
  • The impact of social entrepreneurship on sustainable development
  • The relationship between emotional labor and job burnout
  • The effectiveness of art therapy in treating dementia
  • The correlation between social media use and academic procrastination
  • The effect of poverty on childhood educational attainment
  • The impact of urban green spaces on mental health
  • The relationship between job insecurity and employee well-being
  • The effectiveness of virtual reality exposure therapy in treating anxiety disorders
  • The correlation between childhood trauma and substance abuse
  • The effect of screen time on children’s social skills
  • The impact of trade unions on employee job satisfaction
  • The relationship between cultural intelligence and cross-cultural communication
  • The effectiveness of acceptance and commitment therapy in treating chronic pain
  • The correlation between childhood obesity and adult health outcomes
  • The effect of gender diversity on corporate performance
  • The impact of environmental regulations on industry competitiveness.
  • The impact of renewable energy policies on greenhouse gas emissions
  • The relationship between workplace diversity and team performance
  • The effectiveness of group therapy in treating substance abuse
  • The correlation between parental involvement and social skills in early childhood
  • The effect of technology use on sleep patterns
  • The impact of government regulations on small business growth
  • The relationship between job satisfaction and employee turnover
  • The effectiveness of virtual reality therapy in treating anxiety disorders
  • The correlation between parental involvement and academic motivation in adolescents
  • The effect of social media on political engagement
  • The impact of urbanization on mental health
  • The relationship between corporate social responsibility and consumer trust
  • The correlation between early childhood education and social-emotional development
  • The effect of screen time on cognitive development in young children
  • The impact of trade policies on global economic growth
  • The relationship between workplace diversity and innovation
  • The effectiveness of family therapy in treating eating disorders
  • The correlation between parental involvement and college persistence
  • The effect of social media on body image and self-esteem
  • The impact of environmental regulations on business competitiveness
  • The relationship between job autonomy and job satisfaction
  • The effectiveness of virtual reality therapy in treating phobias
  • The correlation between parental involvement and academic achievement in college
  • The effect of social media on sleep quality
  • The impact of immigration policies on social integration
  • The relationship between workplace diversity and employee well-being
  • The effectiveness of psychodynamic therapy in treating personality disorders
  • The correlation between early childhood education and executive function skills
  • The effect of parental involvement on STEM education outcomes
  • The impact of trade policies on domestic employment rates
  • The relationship between job insecurity and mental health
  • The effectiveness of exposure therapy in treating PTSD
  • The correlation between parental involvement and social mobility
  • The effect of social media on intergroup relations
  • The impact of urbanization on air pollution and respiratory health.
  • The relationship between emotional intelligence and leadership effectiveness
  • The effectiveness of cognitive-behavioral therapy in treating depression
  • The correlation between early childhood education and language development
  • The effect of parental involvement on academic achievement in STEM fields
  • The impact of trade policies on income inequality
  • The relationship between workplace diversity and customer satisfaction
  • The effectiveness of mindfulness-based therapy in treating anxiety disorders
  • The correlation between parental involvement and civic engagement in adolescents
  • The effect of social media on mental health among teenagers
  • The impact of public transportation policies on traffic congestion
  • The relationship between job stress and job performance
  • The effectiveness of group therapy in treating depression
  • The correlation between early childhood education and cognitive development
  • The effect of parental involvement on academic motivation in college
  • The impact of environmental regulations on energy consumption
  • The relationship between workplace diversity and employee engagement
  • The effectiveness of art therapy in treating PTSD
  • The correlation between parental involvement and academic success in vocational education
  • The effect of social media on academic achievement in college
  • The impact of tax policies on economic growth
  • The relationship between job flexibility and work-life balance
  • The effectiveness of acceptance and commitment therapy in treating anxiety disorders
  • The correlation between early childhood education and social competence
  • The effect of parental involvement on career readiness in high school
  • The impact of immigration policies on crime rates
  • The relationship between workplace diversity and employee retention
  • The effectiveness of play therapy in treating trauma
  • The correlation between parental involvement and academic success in online learning
  • The effect of social media on body dissatisfaction among women
  • The impact of urbanization on public health infrastructure
  • The relationship between job satisfaction and job performance
  • The effectiveness of eye movement desensitization and reprocessing therapy in treating PTSD
  • The correlation between early childhood education and social skills in adolescence
  • The effect of parental involvement on academic achievement in the arts
  • The impact of trade policies on foreign investment
  • The relationship between workplace diversity and decision-making
  • The effectiveness of exposure and response prevention therapy in treating OCD
  • The correlation between parental involvement and academic success in special education
  • The impact of zoning laws on affordable housing
  • The relationship between job design and employee motivation
  • The effectiveness of cognitive rehabilitation therapy in treating traumatic brain injury
  • The correlation between early childhood education and social-emotional learning
  • The effect of parental involvement on academic achievement in foreign language learning
  • The impact of trade policies on the environment
  • The relationship between workplace diversity and creativity
  • The effectiveness of emotion-focused therapy in treating relationship problems
  • The correlation between parental involvement and academic success in music education
  • The effect of social media on interpersonal communication skills
  • The impact of public health campaigns on health behaviors
  • The relationship between job resources and job stress
  • The effectiveness of equine therapy in treating substance abuse
  • The correlation between early childhood education and self-regulation
  • The effect of parental involvement on academic achievement in physical education
  • The impact of immigration policies on cultural assimilation
  • The relationship between workplace diversity and conflict resolution
  • The effectiveness of schema therapy in treating personality disorders
  • The correlation between parental involvement and academic success in career and technical education
  • The effect of social media on trust in government institutions
  • The impact of urbanization on public transportation systems
  • The relationship between job demands and job stress
  • The correlation between early childhood education and executive functioning
  • The effect of parental involvement on academic achievement in computer science
  • The effectiveness of cognitive processing therapy in treating PTSD
  • The correlation between parental involvement and academic success in homeschooling
  • The effect of social media on cyberbullying behavior
  • The impact of urbanization on air quality
  • The effectiveness of dance therapy in treating anxiety disorders
  • The correlation between early childhood education and math achievement
  • The effect of parental involvement on academic achievement in health education
  • The impact of global warming on agriculture
  • The effectiveness of narrative therapy in treating depression
  • The correlation between parental involvement and academic success in character education
  • The effect of social media on political participation
  • The impact of technology on job displacement
  • The relationship between job resources and job satisfaction
  • The effectiveness of art therapy in treating addiction
  • The correlation between early childhood education and reading comprehension
  • The effect of parental involvement on academic achievement in environmental education
  • The impact of income inequality on social mobility
  • The relationship between workplace diversity and organizational culture
  • The effectiveness of solution-focused brief therapy in treating anxiety disorders
  • The correlation between parental involvement and academic success in physical therapy education
  • The effect of social media on misinformation
  • The impact of green energy policies on economic growth
  • The relationship between job demands and employee well-being
  • The correlation between early childhood education and science achievement
  • The effect of parental involvement on academic achievement in religious education
  • The impact of gender diversity on corporate governance
  • The relationship between workplace diversity and ethical decision-making
  • The correlation between parental involvement and academic success in dental hygiene education
  • The effect of social media on self-esteem among adolescents
  • The impact of renewable energy policies on energy security
  • The effect of parental involvement on academic achievement in social studies
  • The impact of trade policies on job growth
  • The relationship between workplace diversity and leadership styles
  • The correlation between parental involvement and academic success in online vocational training
  • The effect of social media on self-esteem among men
  • The impact of urbanization on air pollution levels
  • The effectiveness of music therapy in treating depression
  • The correlation between early childhood education and math skills
  • The effect of parental involvement on academic achievement in language arts
  • The impact of immigration policies on labor market outcomes
  • The effectiveness of hypnotherapy in treating phobias
  • The effect of social media on political engagement among young adults
  • The impact of urbanization on access to green spaces
  • The relationship between job crafting and job satisfaction
  • The effectiveness of exposure therapy in treating specific phobias
  • The correlation between early childhood education and spatial reasoning
  • The effect of parental involvement on academic achievement in business education
  • The impact of trade policies on economic inequality
  • The effectiveness of narrative therapy in treating PTSD
  • The correlation between parental involvement and academic success in nursing education
  • The effect of social media on sleep quality among adolescents
  • The impact of urbanization on crime rates
  • The relationship between job insecurity and turnover intentions
  • The effectiveness of pet therapy in treating anxiety disorders
  • The correlation between early childhood education and STEM skills
  • The effect of parental involvement on academic achievement in culinary education
  • The impact of immigration policies on housing affordability
  • The relationship between workplace diversity and employee satisfaction
  • The effectiveness of mindfulness-based stress reduction in treating chronic pain
  • The correlation between parental involvement and academic success in art education
  • The effect of social media on academic procrastination among college students
  • The impact of urbanization on public safety services.

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  • Qualitative vs. Quantitative Research | Differences, Examples & Methods

Qualitative vs. Quantitative Research | Differences, Examples & Methods

Published on April 12, 2019 by Raimo Streefkerk . Revised on June 22, 2023.

When collecting and analyzing data, quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings. Both are important for gaining different kinds of knowledge.

Common quantitative methods include experiments, observations recorded as numbers, and surveys with closed-ended questions.

Quantitative research is at risk for research biases including information bias , omitted variable bias , sampling bias , or selection bias . Qualitative research Qualitative research is expressed in words . It is used to understand concepts, thoughts or experiences. This type of research enables you to gather in-depth insights on topics that are not well understood.

Common qualitative methods include interviews with open-ended questions, observations described in words, and literature reviews that explore concepts and theories.

Table of contents

The differences between quantitative and qualitative research, data collection methods, when to use qualitative vs. quantitative research, how to analyze qualitative and quantitative data, other interesting articles, frequently asked questions about qualitative and quantitative research.

Quantitative and qualitative research use different research methods to collect and analyze data, and they allow you to answer different kinds of research questions.

Qualitative vs. quantitative research

Quantitative and qualitative data can be collected using various methods. It is important to use a data collection method that will help answer your research question(s).

Many data collection methods can be either qualitative or quantitative. For example, in surveys, observational studies or case studies , your data can be represented as numbers (e.g., using rating scales or counting frequencies) or as words (e.g., with open-ended questions or descriptions of what you observe).

However, some methods are more commonly used in one type or the other.

Quantitative data collection methods

  • Surveys :  List of closed or multiple choice questions that is distributed to a sample (online, in person, or over the phone).
  • Experiments : Situation in which different types of variables are controlled and manipulated to establish cause-and-effect relationships.
  • Observations : Observing subjects in a natural environment where variables can’t be controlled.

Qualitative data collection methods

  • Interviews : Asking open-ended questions verbally to respondents.
  • Focus groups : Discussion among a group of people about a topic to gather opinions that can be used for further research.
  • Ethnography : Participating in a community or organization for an extended period of time to closely observe culture and behavior.
  • Literature review : Survey of published works by other authors.

A rule of thumb for deciding whether to use qualitative or quantitative data is:

  • Use quantitative research if you want to confirm or test something (a theory or hypothesis )
  • Use qualitative research if you want to understand something (concepts, thoughts, experiences)

For most research topics you can choose a qualitative, quantitative or mixed methods approach . Which type you choose depends on, among other things, whether you’re taking an inductive vs. deductive research approach ; your research question(s) ; whether you’re doing experimental , correlational , or descriptive research ; and practical considerations such as time, money, availability of data, and access to respondents.

Quantitative research approach

You survey 300 students at your university and ask them questions such as: “on a scale from 1-5, how satisfied are your with your professors?”

You can perform statistical analysis on the data and draw conclusions such as: “on average students rated their professors 4.4”.

Qualitative research approach

You conduct in-depth interviews with 15 students and ask them open-ended questions such as: “How satisfied are you with your studies?”, “What is the most positive aspect of your study program?” and “What can be done to improve the study program?”

Based on the answers you get you can ask follow-up questions to clarify things. You transcribe all interviews using transcription software and try to find commonalities and patterns.

Mixed methods approach

You conduct interviews to find out how satisfied students are with their studies. Through open-ended questions you learn things you never thought about before and gain new insights. Later, you use a survey to test these insights on a larger scale.

It’s also possible to start with a survey to find out the overall trends, followed by interviews to better understand the reasons behind the trends.

Qualitative or quantitative data by itself can’t prove or demonstrate anything, but has to be analyzed to show its meaning in relation to the research questions. The method of analysis differs for each type of data.

Analyzing quantitative data

Quantitative data is based on numbers. Simple math or more advanced statistical analysis is used to discover commonalities or patterns in the data. The results are often reported in graphs and tables.

Applications such as Excel, SPSS, or R can be used to calculate things like:

  • Average scores ( means )
  • The number of times a particular answer was given
  • The correlation or causation between two or more variables
  • The reliability and validity of the results

Analyzing qualitative data

Qualitative data is more difficult to analyze than quantitative data. It consists of text, images or videos instead of numbers.

Some common approaches to analyzing qualitative data include:

  • Qualitative content analysis : Tracking the occurrence, position and meaning of words or phrases
  • Thematic analysis : Closely examining the data to identify the main themes and patterns
  • Discourse analysis : Studying how communication works in social contexts

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

  • Chi square goodness of fit test
  • Degrees of freedom
  • Null hypothesis
  • Discourse analysis
  • Control groups
  • Mixed methods research
  • Non-probability sampling
  • Quantitative research
  • Inclusion and exclusion criteria

Research bias

  • Rosenthal effect
  • Implicit bias
  • Cognitive bias
  • Selection bias
  • Negativity bias
  • Status quo bias

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

The research methods you use depend on the type of data you need to answer your research question .

  • If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
  • If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
  • If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.

There are various approaches to qualitative data analysis , but they all share five steps in common:

  • Prepare and organize your data.
  • Review and explore your data.
  • Develop a data coding system.
  • Assign codes to the data.
  • Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

A research project is an academic, scientific, or professional undertaking to answer a research question . Research projects can take many forms, such as qualitative or quantitative , descriptive , longitudinal , experimental , or correlational . What kind of research approach you choose will depend on your topic.

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Research

98 Quantitative Research Questions & Examples

98 Quantitative Research Questions & Examples

As researchers, we know how powerful quantitative research data can be in helping answer strategic questions. Here, I’ve detailed 23 use cases and curated 98 quantitative market research questions with examples – making this a post you should add to your bookmark list 📚, so you can quickly refer back.

I’ve formatted this post to show you 10-15 questions for each use case. At the end of each section, I also share a quicker way to get similar insights using modern market research tools like Similarweb.

What is a quantitative research question?

Quantitative market research questions tell you the what, how, when, and where of a subject. From trendspotting to identifying patterns or establishing averages– using quantitative data is a clear and effective way to start solving business problems.

Types of quantitative research questions

Quantitative market research questions are divided into two main types: descriptive and causal.

  • Descriptive research questions seek to quantify a phenomenon by focusing on a certain population or phenomenon to measure certain aspects of it, such as frequency, average, or relationship.
  • Causal research questions explore the cause-and-effect relationship between two or more variables.

The ultimate list of questions for quantitative market research

Get clear explanations of the different applications and approaches to quantitative research–with the added bonus of seeing what questions to ask and how they can impact your business.

Examples of quantitative research questions for competitive analysis

A powerful example of quantitative research in play is when it’s used to inform a competitive analysis . A process that’s used to analyze and understand how industry leaders and companies of interest are performing.

Pro Tip: Collect data systematically, and use a competitive analysis framework to record your findings. You can refer back to it when you repeat the process later in the year.

  • What is the market share of our major competitors?
  • What is the average purchase price of our competitors’ products?
  • How often do our competitors release new products?
  • What is the total number of customer reviews for our competitors’ products?
  • What is the average rating of our competitors’ products?
  • What is the average customer satisfaction score for our competitors?
  • What is the average return rate of our competitors’ products?
  • What is the average shipping time for our competitors’ products?
  • What is the average price discount offered by our competitors?
  • What is the average lifespan of our competitors’ products?

With this data, you can determine your position in the market and benchmark your performance against rival companies. It can then be used to improve offerings, service standards, pricing, positioning, and operational effectiveness. Notice that all questions can be answered with a numerical response , a key component of all successful examples of quantitative market research questions.

Quantitative research question example: market analysis

🙋‍♀️ Question: What is the market share of our major competitors?

🤓 Insight sought: Industry market share of leaders and key competitors.

🤯 Challenges with traditional quantitative research methods: Outdated data is a major consideration; data freshness remains critical, yet is often tricky to obtain using traditional research methods. Markets shift fast, so being able to obtain and track market share in real time is a challenge many face.

💡 A new approach: Similarweb enables you to track this key business KPI in real-time using digital data directly from the platform. On any day, you can see what your market share is, along with any players in your market. Plus, you get to see rising stars showing significant growth, who may pose a threat through market disruption or new tactics.

⏰ Time to insight: 30 seconds

✅ How it’s done: Using Similarweb’s Web Industry Analysis, two digital metrics give you the intel needed to decipher the market share in any industry. I’m using the Banking, Credit, and Lending market throughout these examples. I’ve selected the US market, analyzing the performance of the previous 3 months.

  • Share of visits 

quantitative market research example

Here, I can see the top players in my market based on the number of unique visitors to their sites. On top of the raw data that shows me the volume of visitors as a figure, I can quickly see the two players ( Capital One and Chase ) that have grown and by what percentage. On the side, you can see rising players in the industry. Now, while my initial question was to establish the market share of my major competitors, I can see there are a few disruptive players in my market who I’d want to track too; Synchrony.com being one of particular interest, given their substantial growth and traffic numbers.

  • Share of search 

quantitative market research question example

Viewing the overall market size based on total search volumes, you can explore industry leaders in more detail. The top websites are the top five players, ranking by traffic share . You can also view the month-over-month change in visits, which shows you who is performing best at any given time . It’s the same five names, with Paypal and Chase leading the pack. However, I see Wells Fargo is better at attracting repeat visitors, while Capital One and Bank of America perform better at drawing in unique visitors.

In answer to my question, what is the market share of my major competitors, I can quickly use Similarweb’s quantitative data to get my answer.

Traffic distribution breakdown with Similarweb

This traffic share visual can be downloaded from the platform. It plots the ten industry leader’s market share and allocates the remaining share to the rest of the market.

industry leader’s market share quadrant

I can also download a market quadrant analysis, which takes two key data points, traffic share and unique visitors, and plots the industry leaders. All supporting raw data can be downloaded in .xls format or connected to other business intelligence platforms via the API.

Quantitative research questions for consumer behavior studies

These studies measure and analyze consumer behavior, preferences, and habits . Any type of audience analysis helps companies better understand customer intent, and adjust offerings, messaging, campaigns, SEO, and ultimately offer more relevant products and services within a market.

  • What is the average amount consumers spend on a certain product each month?
  • What percentage of consumers are likely to purchase a product based on its price?
  • How do the demographics of the target audience affect their purchasing behavior?
  • What type of incentive is most likely to increase the likelihood of purchase?
  • How does the store’s location impact product sales and turnover?
  • What are the key drivers of product loyalty among consumers?
  • What are the most commonly cited reasons for not buying a product?
  • How does the availability of product information impact purchasing decisions?
  • What is the average time consumers spend researching a product before buying it?
  • How often do consumers use social media when making a purchase decision?

While applying a qualitative approach to such studies is also possible, it’s a great example of quantitative market research in action. For larger corporations, studies that involve a large, relevant sample size of a target market deliver vital consumer insights at scale .

Read More: 83 Qualitative Research Questions & Examples

Quantitative research question and answer: content strategy and analysis

🙋‍♀️ Question: What type of content performed best in the market this past month?

🤓 Insight sought: Establish high-performing campaigns and promotions in a market.

🤯 Challenges with traditional quantitative research methods: Whether you consider putting together a panel yourself, or paying a company to do it for you, quantitative research at scale is costly and time-consuming. What’s more, you have to ensure that sampling is done right and represents your target audience.

💡 A new approach: Data analysis is the foundation of our entire business. For over 10 years, Similarweb has developed a unique, multi-dimensional approach to understanding the digital world. To see the specific campaigns that resonate most with a target audience, use Similarweb’s Popular Pages feature. Key metrics show which campaigns achieve the best results for any site (including rival firms), campaign take-up, and periodic changes in performance and interest.

✅ How it’s done: I’ve chosen Capital One and Wells Fargo to review. Using the Popular Pages campaign filter, I can view all pages identified by a URL parameter UTM. For clarity, I’ve highlighted specific campaigns showing high-growth and increasing popularity. I can view any site’s trending, new, or best-performing pages using a different filter.

popular pages extract Similarweb

In this example, I have highlighted three campaigns showing healthy growth, covering teen checking accounts, performance savings accounts, and add-cash-in-store. Next, I will perform the same check for another key competitor in my market.

Wells Fargo popular pages extract Similarweb

Here, I can see financial health tools campaigns with over 300% month-over-month growth and smarter credit and FICO campaigns showing strong performance. This tells me that campaigns focussing on education and tools are growing in popularity within this market. 

Examples of quantitative research questions for brand tracking

These studies are designed to measure customers’ awareness, perceptions, behaviors, and attitudes toward a brand over time. Different applications include measuring brand awareness , brand equity, customer satisfaction, and purchase or usage intent.

quantitative research questions for brand tracking

These types of research surveys ask questions about brand knowledge, brand attributes, brand perceptions, and brand loyalty . The data collected can then be used to understand the current state of a brand’s performance, identify improvements, and track the success of marketing initiatives.

  • To what extent is Brand Z associated with innovation?
  • How do consumers rate the quality of Brand Z’s products and services?
  • How has the awareness of Brand Z changed over the past 6 months?
  • How does Brand Z compare to its competitors in terms of customer satisfaction?
  • To what extent do consumers trust Brand Z?
  • How likely are consumers to recommend Brand Z?
  • What factors influence consumers’ purchase decisions when considering Brand Z?
  • What is the average customer satisfaction score for equity?
  • How does equity’s customer service compare to its competitors?
  • How do customer perceptions of equity’s brand values compare to its competitors?

Quantitative research question example and answer: brand tracking

🙋‍♀️ Question: How has the awareness of Brand Z changed over the past 6 months?

🤓 Insight sought: How has brand awareness changed for my business and competitors over time.

⏰ Time to insight: 2 minutes

✅ How it’s done: Using Similarweb’s search overview , I can quickly identify which brands in my chosen market have the highest brand awareness over any time period or location. I can view these stats as a custom market or examine brands individually.

Quantitative research questions example for brand awareness

Here, I’ve chosen a custom view that shows me five companies side-by-side. In the top right-hand corner, under branded traffic, you get a quick snapshot of the share of website visits that were generated by branded keywords. A branded keyword is when a consumer types the brand name + a search term.

Below that, you will see the search traffic and engagement section. Here, I’ve filtered the results to show me branded traffic as a percentage of total traffic. Similarweb shows me how branded search volumes grow or decline monthly. Helping me answer the question of how brand awareness has changed over time.

Quantitative research questions for consumer ad testing

Another example of using quantitative research to impact change and improve results is ad testing. It measures the effectiveness of different advertising campaigns. It’s often known as A/B testing , where different visuals, content, calls-to-action, and design elements are experimented with to see which works best. It can show the impact of different ads on engagement and conversions.

A range of quantitative market research questions can be asked and analyzed to determine the optimal approach.

  • How does changing the ad’s headline affect the number of people who click on the ad?
  • How does varying the ad’s design affect its click-through rate?
  • How does altering the ad’s call-to-action affect the number of conversions?
  • How does adjusting the ad’s color scheme influence the number of people who view the ad?
  • How does manipulating the ad’s text length affect the average amount of time a user spends on the landing page?
  • How does changing the ad’s placement on the page affect the amount of money spent on the ad?
  • How does varying the ad’s targeting parameters affect the number of impressions?
  • How does altering the ad’s call-to-action language impact the click-through rate?

Quantitative question examples for social media monitoring

Quantitative market research can be applied to measure and analyze the impact of social media on a brand’s awareness, engagement, and reputation . By tracking key metrics such as the number of followers, impressions, and shares, brands can:

  • Assess the success of their social media campaigns
  • Understand what content resonates with customers
  • Spot potential areas for improvement
  • How often are people talking about our brand on social media channels?
  • How many times has our brand been mentioned in the past month?
  • What are the most popular topics related to our brand on social media?
  • What is the sentiment associated with our brand across social media channels?
  • How do our competitors compare in terms of social media presence?
  • What is the average response time for customer inquiries on social media?
  • What percentage of followers are actively engaging with our brand?
  • What are the most popular hashtags associated with our brand?
  • What types of content generate the most engagement on social media?
  • How does our brand compare to our competitors in terms of reach and engagement on social media?

Example of quantitative research question and answer: social media monitoring

🙋‍♀️ Question: How does our brand compare to our competitors in terms of reach and engagement on social media?

🤓 Insight sought: The social channels that most effectively drive traffic and engagement in my market

✅ How it’s done: Similarweb Digital Research Intelligence shows you a marketing channels overview at both an industry and market level. With it, you can view the most effective social media channels in any industry and drill down to compare social performance across a custom group of competitors or an individual company.

Here, I’ve taken the five closest rivals in my market and clicked to expand social media channel data. Wells Fargo and Bank of America have generated the highest traffic volume from social media, with over 6.6 million referrals this year. Next, I can see the exact percentage of traffic generated by each channel and its relative share of traffic for each competitor. This shows me the most effective channels are Youtube, Facebook, LinkedIn, and Reddit – in that order.

Quantitative social media questions

In 30-seconds, I’ve discovered the following:

  • YouTube is the most popular social network in my market.
  • Facebook and LinkedIn are the second and third most popular channels.
  • Wells Fargo is my primary target for a more in-depth review, with the highest performance on the top two channels.
  • Bank of America is outperforming all key players significantly on LinkedIn.
  • American Express has found a high referral opportunity on Reddit that others have been unable to match.

Power-up Your Market Research with Similarweb Today

Examples of quantitative research questions for online polls.

This is one of the oldest known uses of quantitative market research. It dates back to the 19th century when they were first used in America to try and predict the outcome of the presidential elections.

quantitative research questions for online polls

Polls are just short versions of surveys but provide a point-in-time perspective across a large group of people. You can add a poll to your website as a widget, to an email, or if you’ve got a budget to spend, you might use a company like YouGov to add questions to one of their online polls and distribute it to an audience en-masse.

  • What is your annual income?
  • In what age group do you fall?
  • On average, how much do you spend on our products per month?
  • How likely are you to recommend our products to others?
  • How satisfied are you with our customer service?
  • How likely are you to purchase our products in the future?
  • On a scale of 1 to 10, how important is price when it comes to buying our products?
  • How likely are you to use our products in the next six months?
  • What other brands of products do you purchase?
  • How would you rate our products compared to our competitors?

Quantitative research questions for eye tracking studies

These research studies measure how people look and respond to different websites or ad elements. It’s traditionally an example of quantitative research used by enterprise firms but is becoming more common in the SMB space due to easier access to such technologies.

  • How much time do participants spend looking at each visual element of the product or ad?
  • How does the order of presentation affect the impact of time spent looking at each visual element?
  • How does the size of the visual elements affect the amount of time spent looking at them?
  • What is the average time participants spend looking at the product or ad as a whole?
  • What is the average number of fixations participants make when looking at the product or ad?
  • Are there any visual elements that participants consistently ignore?
  • How does the product’s design or advertising affect the average number of fixations?
  • How do different types of participants (age, gender, etc.) interact with the product or ad differently?
  • Is there a correlation between the amount of time spent looking at the product or ad and the participants’ purchase decision?
  • How does the user’s experience with similar products or ads affect the amount of time spent looking at the current product or ad?

Quantitative question examples for customer segmentation

Segmentation is becoming more important as organizations large and small seek to offer more personalized experiences. Effective segmentation helps businesses understand their customer’s needs–which can result in more targeted marketing, increased conversions, higher levels of loyalty, and better brand awareness.

quantitative research questions for segmentation

If you’re just starting to segment your market, and want to know the best quantitative research questions to ask to help you do this, here are 20 to choose from.

Examples of quantitative research questions to segment customers

  • What is your age range?
  • What is your annual household income?
  • What is your preferred online shopping method?
  • What is your occupation?
  • What types of products do you typically purchase?
  • Are you a frequent shopper?
  • How often do you purchase products online?
  • What is your typical budget for online purchases?
  • What is your primary motivation for purchasing products online?
  • What factors influence your decision to purchase a product online?
  • What device do you use most often when shopping online?
  • What type of product categories are you most interested in?
  • Do you prefer to shop online for convenience or for a better price?
  • What type of discounts or promotions do you look for when making online purchases?
  • How do you prefer to receive notifications about product promotions or discounts?
  • What type of payment methods do you prefer when shopping online?
  • What methods do you use to compare different products and prices when shopping online?
  • What type of customer service do you expect when shopping online?
  • What type of product reviews do you consider when making online purchases?
  • How do you prefer to interact with a brand when shopping online?

Examples of quantitative research questions for analyzing customer segments

  • What is the average age of customers in each segment?
  • How do spending habits vary across customer segments?
  • What is the average length of time customers spend in each segment?
  • How does loyalty vary across customer segments?
  • What is the average purchase size in each segment?
  • What is the average frequency of purchases in each segment?
  • What is the average customer lifetime value in each segment?
  • How does customer satisfaction vary across customer segments?
  • What is the average response rate to campaigns in each segment?
  • How does customer engagement vary across customer segments?

These questions are ideal to ask once you’ve already defined your segments. We’ve written a useful post that covers the ins and outs of what market segmentation is and how to do it.

Additional applications of quantitative research questions

I’ve covered ten use cases for quantitative questions in detail. Still, there are other instances where you can put quantitative research to good use.

Product usage studies: Measure how customers use a product or service.

Preference testing: Testing of customer preferences for different products or services.

Sales analysis: Analysis of sales data to identify trends and patterns.

Distribution analysis: Analyzing distribution channels to determine the most efficient and effective way to reach customers.

Focus groups: Groups of consumers brought together to discuss and provide feedback on a particular product, service, or marketing campaign.

Consumer interviews: Conducted with customers to understand their behavior and preferences better.

Mystery shopping: Mystery shoppers are sent to stores to measure customer service levels and product availability.

Conjoint analysis: Analysis of how consumers value different attributes of a product or service.

Regression analysis: Statistical analysis used to identify relationships between different variables.

A/B testing: Testing two or more different versions of a product or service to determine which one performs better.

Brand equity studies: Measure, compare and analyze brand recognition, loyalty, and consumer perception.

Exit surveys: Collect numerical data to analyze employee experience and reasons for leaving, providing insight into how to improve the work environment and retain employees.

Price sensitivity testing: Measuring responses to different pricing models to find the optimal pricing model, and identify areas if and where discounts or incentives might be beneficial.

Quantitative market research survey examples

A recent GreenBook study shows that 89% of people in the market research industry use online surveys frequently–and for good reason. They’re quick and easy to set up, the cost is minimal, and they’re highly scalable too.

Quantitative market research method examples

Questions are always formatted to provide close-ended answers that can be quantified. If you wish to collect free-text responses, this ventures into the realm of qualitative research . Here are a few examples.

Brand Loyalty Surveys: Companies use online surveys to measure customers’ loyalty to their brand. They include questions about how long an individual has been a customer, their overall satisfaction with the service or product, and the likelihood of them recommending the brand to others.

Customer Satisfaction Surveys: These surveys may include questions about the customer’s experience, their overall satisfaction, and the likelihood they will recommend a product or service to others.

Pricing Studies: This type of research reveals how customers value their products or services. These surveys may include questions about the customer’s willingness to pay for the product, the customer’s perception of the price and value, and their comparison of the price to other similar items.

Product/Service Usage Studies: These surveys measure how customers use their products or services. They can include questions about how often customers use a product, their preferred features, and overall satisfaction.

Here’s an example of a typical survey we’ve used when testing out potential features with groups of clients. After they’ve had the chance to use the feature for a period, we send a short survey, then use the feedback to determine the viability of the feature for future release.

Employee Experience Surveys: Another great example of quantitative data in action, and one we use at Similarweb to measure employee satisfaction. Many online platforms are available to help you conduct them; here, we use Culture AMP . The ability to manipulate the data, spot patterns or trends, then identify the core successes and development areas are astounding.

Qualitative customer experience example Culture AMP

Read a connected post that shows 18 ways to use market research surveys .

How to answer quantitative research questions with Similarweb

For the vast majority of applications I’ve covered in this post, there’s a more modern, quicker, and more efficient way to obtain similar insights online. Gone are the days when companies need to use expensive outdated data or pay hefty sums of money to market research firms to conduct broad studies to get the answers they need.

By this point, I hope you’ve seen how quick and easy it is to use Similarweb to do market research the modern way. But I’ve only scratched the surface of its capabilities.

Take two to watch this introductory video and see what else you can uncover.

Added bonus: Similarweb API

If you need to crunch large volumes of data and already use tools like Tableau or PowerBI, you can seamlessly connect Similarweb via the API and pipe in the data. So for faster analysis of big data, you can leverage Similarweb data to use alongside the visualization tools you already know and love.

Similarweb’s suite of market intelligence solutions offers unbiased, accurate, honest insights you can trust. With a world of data at your fingertips, use Similarweb Digital Research Intelligence to uncover telling facts that help inform your research and strengthen your position.

Use it for:

Market Research

Benchmarking

Audience Insights

Company Research

Consumer Journey Tracking

Wrapping up

Today’s markets change at lightning speed. To keep up and succeed, companies need access to insights and intel they can depend on to be timely and on-point. While quantitative market research questions can and should always be asked, it’s important to leverage technology to increase your speed to insight, and thus improve reaction times and response to market shifts.

What is quantitative market research?

Quantitative market research is a form of research that uses numerical data to gain insights into the behavior and preferences of customers. It is used to measure and track the performance of products, services, and campaigns.

How does quantitative market research help businesses?

Quantitative market research can help businesses identify customer trends, measure customer satisfaction, and develop effective marketing strategies. It can also provide valuable insights into customer behavior, preferences, and attitudes.

What types of questions should be included in a quantitative market research survey?

Questions in a quantitative market research survey should be focused, clear, and specific. Questions should be structured to collect quantitative data, such as numbers, percentages, or frequency of responses.

What methods can be used to collect quantitative market research data?

Common methods used to collect quantitative market research data include surveys, interviews, focus groups, polls, and online questionnaires.

What are the advantages and disadvantages of using quantitative market research?

The advantages of using quantitative market research include the ability to collect data quickly, the ability to analyze data in a structured way, and the ability to identify trends. Disadvantages include the potential for bias, the cost of collecting data, and the difficulty in interpreting results.

Related Posts

How to Conduct a Social Media Competitor Analysis: 5 Quick Steps

How to Conduct a Social Media Competitor Analysis: 5 Quick Steps

Industry Research: The Data-Backed Approach

Industry Research: The Data-Backed Approach

How to Do a Competitive Analysis: A Complete Guide

How to Do a Competitive Analysis: A Complete Guide

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quantitative research essay questions

  • A/B Monadic Test
  • A/B Pre-Roll Test
  • Key Driver Analysis
  • Multiple Implicit
  • Penalty Reward
  • Price Sensitivity
  • Segmentation
  • Single Implicit
  • Category Exploration
  • Competitive Landscape
  • Consumer Segmentation
  • Innovation & Renovation
  • Product Portfolio
  • Marketing Creatives
  • Advertising
  • Shelf Optimization
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  • Better Brand Health Tracking
  • Ad Tracking
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  • AI Insights
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What Are Quantitative Survey Questions? Types and Examples

diagonal green and purple lines with black background

Table of contents: 

  • Types of quantitative survey questions - with examples 
  • Quantitative question formats
  • How to write quantitative survey questions 
  • Examples of quantitative survey questions 

Leveraging quantilope for your quantitative survey 

In a quantitative research study brands will gather numeric data for most of their questions through formats like numerical scale questions or ranking questions. However, brands can also include some non-quantitative questions throughout their quantitative study - like open-ended questions, where respondents will type in their own feedback to a question prompt. Even so, open-ended answers can be numerically coded to sift through feedback easily (e.g. anyone who writes in 'Pepsi' in a soda study would be assigned the number '1', to look at Pepsi feedback as a whole).  One of the biggest benefits of using a quantitative research approach is that insights around a research topic can undergo statistical analysis; the same can’t be said for qualitative data like focus group feedback or interviews. Another major difference between quantitative and qualitative research methods is that quantitative surveys require respondents to choose from a limited number of choices in a close-ended question - generating clear, actionable takeaways. However, these distinct quantitative takeaways often pair well with freeform qualitative responses - making quant and qual a great team to use together.  The rest of this article focuses on quantitative research, taking a closer look at quantitative survey question types and question formats/layouts. 

Back to table of contents 

Types of dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139745">quantitative survey questions - with examples 

Quantitative questions come in many forms, each with different benefits depending on dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139784">your dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139740">market research objectives. Below we’ll explore some of these dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139745">quantitative dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139785">survey question dropdown#toggle" data-dropdown-menu-id-param="menu_term_281139785" data-dropdown-placement-param="top" data-term-id="281139785"> types, which are commonly used together in a single survey to keep things interesting for dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents . The style of questioning used during dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139739">quantitative dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139750">data dropdown#toggle" data-dropdown-menu-id-param="menu_term_281139750" data-dropdown-placement-param="top" data-term-id="281139750"> collection is important, as a good mix of the right types of questions will deliver rich data, limit dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondent fatigue, and optimize the dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139757">response rate . dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139742">Questionnaires should be enjoyable - and varying the dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139755">types of dropdown#toggle" data-dropdown-menu-id-param="menu_term_281139755" data-dropdown-placement-param="top" data-term-id="281139755">quantitative research dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139755"> questions used throughout your survey will help achieve that. 

Descriptive survey questions

dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139763">Descriptive research questions (also known as usage and attitude, or, U&A questions) seek a general indication or prediction about how a dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139773">group of people behaves or will behave, how that group is characterized, or how a group thinks.

For example, a business might want to know what portion of adult men shave, and how often they do so. To find this out, they will survey men (the dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139743">target audience ) and ask descriptive questions about their frequency of shaving (e.g. daily, a few times a week, once per week, and so on.) Each of these frequencies get assigned a numerical ‘code’ so that it’s simple to chart and analyze the data later on; daily might be assigned ‘5’, a few times a week might be assigned ‘4’, and so on. That way, brands can create charts using the ‘top two’ and ‘bottom two’ values in a descriptive question to view these metrics side by side.

Another business might want to know how important local transit issues are to residents, so dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139745">quantitative survey questions will allow dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents to indicate the degrees of opinion attached to various transit issues. Perhaps the transit business running this survey would use a sliding numeric scale to see how important a particular issue is.

Comparative survey questions

dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139782">Comparative research questions are concerned with comparing individuals or groups of people based on one or more variables. These questions might be posed when a business wants to find out which segment of its dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139743">target audience might be more profitable, or which types of products might appeal to different sets of consumers.

For example, a business might want to know how the popularity of its chocolate bars is spread out across its entire customer base (i.e. do women prefer a certain flavor? Are children drawn to candy bars by certain packaging attributes? etc.). Questions in this case will be designed to profile and ‘compare’ segments of the market.

Other businesses might be looking to compare coffee consumption among older and younger consumers (i.e. dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139741">demographic segments), the difference in smartphone usage between younger men and women, or how women from different regions differ in their approach to skincare.

Relationship-based survey questions

As the name suggests, relationship-based survey questions are concerned with the relationship between two or more variables within one or more dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139741">demographic groups. This might be a dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139759">causal link between one thing and the other - for example, the consumption of caffeine and dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents ’ reported energy levels throughout the day. In this case, a coffee or energy drink brand might be interested in how energy levels differ between those who drink their caffeinated line of beverages and those who drink decaf/non-caffeinated beverages.

Alternatively, it might be a case of two or more factors co-existing, without there necessarily being a dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139759">causal link - for example, a particular type of air freshener being more popular amongst a certain dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139741">demographic (maybe one that is controlled wirelessly via Bluetooth is more popular among younger homeowners than one that’s plugged into the wall with no controls). Knowing that millennials favor air fresheners which have options for swapping out scents and setting up schedules would be valuable information for new product development.

Advanced method survey questions

Aside from descriptive, comparative, and relationship-based survey questions, brands can opt to include advanced methodologies in their quantitative dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139742">questionnaire for richer depth. Though advanced methods are more complex in terms of the insights output, quantilope’s Consumer Intelligence Platform automates the setup and analysis of these methods so that researchers of any background or skillset can leverage them with ease.

With quantilope’s pre-programmed suite of 12 advanced methodologies , including MaxDiff , TURF , Implicit , and more, users can drag and drop any of these into a dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139742">questionnaire and customize for their own dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139740">market research objectives.

For example, consider a beverage company that’s looking to expand its flavor profiles. This brand would benefit from a MaxDiff which forces dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents to make tradeoff decisions between a set of flavors. A dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondent might say that coconut is their most-preferred flavor, and lime their least (when in a consideration set with strawberry), yet later on in the MaxDiff that same dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondent may say Strawberry is their most-preferred flavor (over black cherry and kiwi). While this is just one example of an advanced method, instantly you can see how much richer and more actionable these quantitative metrics become compared to a standard usage and attitude question .

Advanced methods can be used alongside descriptive, comparison, or relationship questions to add a new layer of context wherever a business sees fit. Back to table of contents 

Quantitative question formats  

So we’ve covered the kinds of dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139736">quantitative research questions you might want to answer using dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139740">market research , but how do these translate into the actual format of questions that you might include on your dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139742">questionnaire ?

Thinking ahead to your reporting process during your dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139742">questionnaire setup is actually quite important, as the available chart types differ among the types of questions asked; some question data is compatible with bar chart displays, others pie charts, others in trended line graphs, etc. Also consider how well the questions you’re asking will translate onto different devices that your dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents might be using to complete the survey (mobile, PC, or tablet).

Single Select questions

Single select questions are the simplest form of quantitative questioning, as dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents are asked to choose just one answer from a list of items, which tend to be ‘either/or’, ‘yes/no’, or ‘true/false’ questions. These questions are useful when you need to get a clear answer without any qualifying nuances.

yesno

Multi-select questions

Multi-select questions (aka, dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139767">multiple choice ) offer more flexibility for responses, allowing for a number of responses on a single question. dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">Respondents can be asked to ‘check all that apply’ or a cap can be applied (e.g. ‘select up to 3 choices’).

For example:

multiselect

Aside from asking text-based questions like the above examples, a brand could also use a single or multi-select question to ask respondents to select the image they prefer more (like different iterations of a logo design, packaging options, branding colors, etc.). 

dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139749">Likert dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139766">scale dropdown#toggle" data-dropdown-menu-id-param="menu_term_281139766" data-dropdown-placement-param="top" data-term-id="281139766"> questions

A dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139749">Likert scale   is widely used as a convenient and easy-to-interpret rating method. dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">Respondents find it easy to indicate their degree of feelings by selecting the response they most identify with.

likertscale

Slider scales

Slider scales are another good interactive way of formatting questions. They allow dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents to customize their level of feeling about a question, with a bit more variance and nuance allowed than a numeric scale:

logo slider scale example

One particularly common use of a slider scale in a dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139740">market dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139770">research dropdown#toggle" data-dropdown-menu-id-param="menu_term_281139770" data-dropdown-placement-param="top" data-term-id="281139770"> study is known as a NPS (Net Promoter Score) - a way to measure dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139775">customer experience and loyalty . A 0-10 scale is used to ask customers how likely they are to recommend a brand’s product or services to others. The NPS score is calculated by subtracting the percentage of ‘detractors’ (those who respond with a 0-6) from the percentage of promoters (those who respond with a 9-10). dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">Respondents who select 7-8 are known as ‘passives’.

For example: 

nps

Drag and drop questions

Drag-and-drop question formats are a more ‘gamified’ approach to survey capture as they ask dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents to do more than simply check boxes or slide a scale. Drag-and-drop question formats are great for ranking exercises - asking dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents to place answer options in a certain order by dragging with their mouse. For example, you could ask survey takers to put pizza toppings in order of preference by dragging options from a list of possible answers to a box displaying their personal preferences:

ranking poster

Matrix questions

Matrix   questions are a great way to consolidate a number of questions that ask for the same type of response (e.g. single select yes/no, true/false, or multi-select lists). They are mutually beneficial - making a survey look less daunting for the dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondent , and easier for a brand to set up than asking multiple separate questions.

Items in a matrix question are presented one by one, as respondents cycle through the pages selecting one answer for each coffee flavor shown. 

Untitled design (5)-1

While the above example shows a single-matrix question - meaning a respondent can only select one answer per element (in this case, coffee flavors), a matrix setup can also be used for multiple-choice questions - allowing respondents to choose multiple answers per element shown, or for rating questions - allowing respondents to assign a rating (e.g. 1-5) for a list of elements at once.  Back to table of contents 

How to write dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139745">quantitative survey questions  

We’ve reviewed the types of questions you might ask in a quantitative survey, and how you might format those questions, but now for the actual crafting of the content.

When considering which questions to include in your survey, you’ll first want to establish what your research goals are and how these relate to your business goals. For example, thinking about the three types of dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139745">quantitative survey questions explained above - descriptive, comparative, and relationship-based - which type (or which combination) will best meet your research needs? The questions you ask dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents may be phrased in similar ways no matter what kind of layout you leverage, but you should have a good idea of how you’ll want to analyze the results as that will make it much easier to correctly set up your survey.

Quantitative questions tend to start with words like ‘how much,’ ‘how often,’ ‘to what degree,’ ‘what do you think of,’ ‘which of the following’ - anything that establishes what consumers do or think and that can be assigned a numerical code or value. Be sure to also include ‘other’ or ‘none of the above’ options in your quant questions, accommodating those who don’t feel the pre-set answers reflect their true opinion. As mentioned earlier, you can always include a small number of dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139748">open-ended questions in your quant survey to account for any ideas or expanded feedback that the pre-coded questions don’t (or can’t) cover. Back to table of contents 

Examples of dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139745">quantitative survey questions  

dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139745">Quantitative survey questions impose limits on the answers that dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents can choose from, and this is a good thing when it comes to measuring consumer opinions on a large scale and comparing across dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents . A large volume of freeform, open-ended answers is interesting when looking for themes from qualitative studies, but impractical to wade through when dealing with a large dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139756">sample size , and impossible to subject to dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139774">statistical analysis .

For example, a quantitative survey might aim to establish consumers' smartphone habits. This could include their frequency of buying a new smartphone, the considerations that drive purchase, which features they use their phone for, and how much they like their smartphone.

Some examples of quantitative survey questions relating to these habits would be:

Q. How often do you buy a new smartphone?

[single select question]

More than once per year

Every 1-2 years

Every 3-5 years

Every 6+ years

Q. Thinking about when you buy a smartphone, please rank the following factors in order of importance:

[drag and drop ranking question]

screen size

storage capacity

Q. How often do you use the following features on your smartphone?

[matrix question]

Q. How do you feel about your current smartphone?

[sliding scale]

I love it <-------> I hate it

Answers from these above questions, and others within the survey, would be analyzed to paint a picture of smartphone usage and attitude trends across a population and its sub-groups. dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139738">Qualitative research might then be carried out to explore those findings further - for example, people’s detailed attitudes towards their smartphones, how they feel about the amount of time they spend on it, and how features could be improved. Back to table of contents 

quantilope’s Consumer Intelligence Platform specializes in automated, advanced survey insights so that researchers of any skill level can benefit from quick, high-quality consumer insights. With 12 advanced methods to choose from and a wide variety of quantitative question formats, quantilope is your one-stop-shop for all things dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139740">market research (including its dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139776">in-depth dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139738">qualitative research solution - inColor ).

When it comes to building your survey, you decide how you want to go about it. You can start with a blank slate and drop questions into your survey from a pre-programmed list, or you can get a head start with a survey dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139765">template for a particular business use case (like concept testing ) and customize from there. Once your survey is ready to launch, simply specify your dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139743">target audience , connect any panel (quantilope is panel agnostic), and watch as dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139783">answer questions in your survey in real-time by monitoring the fieldwork section of your project. AI-driven dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139764">data analysis takes the raw data and converts it into actionable findings so you never have to worry about manual calculations or statistical testing.

Whether you want to run your quantitative study entirely on your own or with the help of a classically trained research team member, the choice is yours on quantilope’s platform. For more information on how quantilope can help with your next dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139736">quantitative dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139768">research dropdown#toggle" data-dropdown-menu-id-param="menu_term_281139768" data-dropdown-placement-param="top" data-term-id="281139768"> project , get in touch below!

Get in touch to learn more about quantitative research with quantilope!

Related posts, how to use ai for automated data analysis and visualization, how to select a top-tier market research technology, quantilope welcomes chief financial officer, tom fencl, new quantilope academy course: designing optimal and effective surveys.

quantitative research essay questions

Essay on Qualitative vs. Quantitative Research

Both qualitative and quantitative researches are valued in the research world and are often used together under a single project. This is despite the fact that they have significant differences in terms of their theoretical, epistemological, and methodological formations. Qualitative research is usually in form of words while quantitative research takes the numerical approach. This paper discusses the similarities, differences, advantages, and disadvantages of qualitative and quantitative research and provides a personal stand.

Similarities

Both qualitative and quantitative research approaches begin with a problem on which scholars seek to find answers. Without a research problem or question, there would be no reason for carrying out the study. Once a problem is formulated, researchers at their own discretion and depending on the nature of the question choose the appropriate type of research to employ. Just like in qualitative research, data obtained from quantitative analysis need to be analyzed (Miles & Huberman, 1994). This step is crucial for helping researchers to gain a deeper understanding of the issue under investigation. The findings of any research enjoy confirmability after undergoing a thorough examination and auditing process (Miles & Huberman, 1994).

Both types of research approaches require a concise plan before they are carried out. Once researchers formulate the study question, they must come up with a plan for investigating the matter (Yilmaz, 2013). Such plans include deciding the appropriate research technique to implement, estimating budgets, and deciding on the study areas. Failure to plan before embarking on the research project may compromise the research findings. In addition, both qualitative and quantitative research are dependent on each other and can be used for a single research project (Miles & Huberman, 1994). Quantitative data helps the qualitative research in finding a representative study sample and obtaining the background data. In the same way, qualitative research provides the quantitative side with the conceptual development and instrumentation (Miles & Huberman, 1994).

Differences

Qualitative research seeks to explain why things are the way they seem to be. It provides well-grounded descriptions and explanations of processes in identifiable local contexts (Miles & Huberman, 1994). Researchers use qualitative research to dig deeper into the problem and develop a relevant hypothesis for potential quantitative research. On the other hand, Quantitative research uses numerical data to state and quantify the problem (Yilmaz, 2013). Researchers in quantitative research use measurable data in formulating facts and uncovering the research pattern.

Quantitative research approach involves a larger number of participants for the purpose of gathering as much information as possible to summarize characteristics across large groups. This makes it a very expensive research approach. On the contrary, qualitative research approach describes a phenomenon in a more comprehensive manner. A relatively small number of participants take part in this type of research. This makes the overall process cheaper and time friendly.

Data collection methods differ significantly in the two research approaches. In quantitative research, scholars use surveys, questionnaires, and systematic measurements that involve numbers (Yilmaz, 2013). Moreover, they report their findings in impersonal third person prose by using numbers. This is different from the qualitative approach where only the participants’ observation and deep document analysis is necessary for conclusions to be drawn. Findings are disseminated in the first person’s narrative with sufficient quotations from the participants.

Advantages and Disadvantages of Qualitative Research

Qualitative data is based on human observations. Respondent’s observations connect the researcher to the most basic human experiences (Rahman, 2016). It gives a detailed production of participants’ opinions and feelings and helps in efficient interpretation of their actions (Miles & Huberman, 1994). Moreover, this research approach is interdisciplinary and entails a wide range of research techniques and epistemological viewpoints. Data collection methods in qualitative approach are both detailed and subjective (Rahman, 2016). Direct observations, unstructured interviews, and participant observation are the most common techniques employed in this type of research. Researchers have the opportunity to mingle directly with the respondents and obtain first-hand information.

On the negative side, the smaller population sample used in qualitative research raises credibility concerns (Rahman, 2016). The views of a small group of respondents may not necessarily reflect those of the entire population. Moreover, conducting this type of research on certain aspects such as the performance of students may be more challenging. In such instances, researchers prefer to use the quantitative approach instead (Rahman, 2016). Data analysis and interpretation in qualitative research is a more complex process. It is long, has elusive data, and has very stringent requirements for analysis (Rahman, 2016). In addition, developing a research question in this approach is a challenging task as the refining question mostly becomes continuous throughout the research process.

Advantages and Disadvantages of Quantitative Research

The findings of a quantitative research can be generalized to a whole population as it involves larger samples that are randomly selected by researchers (Rahman, 2016). Moreover, the methods used allows for use of statistical software in test taking (Rahman, 2016). This makes the approach time effective and efficient for tackling complex research questions. Quantitative research allows for objectivity and accuracy of the study results. This approach is well designed to provide essential information that supports generalization of a phenomenon under study. It involves few variables and many cases that guarantee the validity and credibility of the study results.

This research approach, however, has some limitations. There is a limited direct connection between the researcher and respondents. Scholars who adopt this approach measure variables at specific moments in time and disregards the past experiences of the respondents (Rahman, 2016). As a result, deep information is often ignored and only the overall picture of the variables is represented. The quantitative approach uses standard questions set and administered by researchers (Rahman, 2016). This might lead to structural bias by respondents and false representation. In some instances, data may only reflect the views of the sample under study instead of revealing the real situation. Moreover, preset questions and answers limit the freedom of expression by the respondents.

Preferred Method

I would prefer quantitative research method over the qualitative approach. Data management in this technique is much familiar and more accessible to researchers’ contexts (Miles & Huberman, 1994). It is a more scientific process that involves the collection, analysis, and interpretation of large amounts of data. Researchers have more control of the manner in which data is collected. Unlike qualitative data that requires descriptions, quantitative approach majors on numerical data (Yilmaz, 2013). With this type of data, I can use the various available software for classification and analyzes. Moreover, researchers are more flexible and free to interact with respondents. This gives an opportunity for obtaining first-hand information and learning more about other behavioral aspects of the population under study.

As highlighted above, qualitative and quantitative techniques are the two research approaches. Both seek to dig deeper into a particular problem, analyze the responses of a selected sample and make viable conclusions. However, qualitative research is much concerned with the description of peoples’ opinions, motivations, and reasons for a particular phenomenon. On the other hand, Quantitative research uses numerical data to state and explain research findings. Use of numerical data allows for objectivity and accuracy of the research results. However structural biases are common in this approach. Data collection and sampling in qualitative research is more detailed and subjective. Considering the different advantages and disadvantages of the two research approaches, I would go for the quantitative over qualitative research.

Miles, M., & Huberman, A. (1994).  Qualitative data analysis  (2nd Ed.). Beverly Hills: Sage.

Rahman, M. (2016). The Advantages and Disadvantages of Using Qualitative and Quantitative Approaches and Methods in Language “Testing and Assessment” Research: A Literature Review.  Journal of Education and Learning , 6(1), 102.

Yilmaz, K. (2013). Comparison of Quantitative and Qualitative Research Traditions: epistemological, theoretical, and methodological differences.  European Journal of Education , 48(2), 311-325.

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Research Question Generator for Free

If you’re looking for the best research question generator, you’re in the right place. Get a list of ideas for your essay, research paper, or any other project with this online tool.

  • 🎓 How to Use the Tool
  • 🤔 What Is a Research Question?
  • 😺 Research Question Examples
  • 👣 Steps to Making a Research Question

📝 Research Question Maker: the Benefits

🔗 references, 🎓 research question generator: how to use it.

Research can’t be done without a clear purpose, an intention behind it.

This intention is usually reflected in a research question, which indicates how you approach your study topic.

If you’re unsure how to write a good research question or are new to this process, you’ll surely benefit from our free online tool. All you need is:

  • Indicate your search term or title
  • Stipulate the subject or academic area
  • Press “Generate questions”
  • Choose a suitable research question from the generated list.

As you can see, this is the best research question generator requiring minimal input for smart question formulation. Try it out to see how simple the process is.

🤔 Why Make an Inquiry Question?

A research question is a question that you formulate for your scientific inquiry . It is a question that sets the scope for your study and determines how you will approach the identified problem, gap, or issue.

Questions can be descriptive , meaning they aim to describe or measure a subject of the researcher's interest.

Otherwise, they can be exploratory , focusing on the under-researched areas and aiming to expand the existing research evidence on the topic.

If there's enough knowledge about the subject, and you want to dig deeper into the existing trends and relationships, you can also use an explanatory research question.

What Makes a Strong Research Question?

The strength of your formulated research question determines the quality of your research, whether it’s a short argumentative essay or an extensive research paper . So, you should review the quality of your question before conducting the full-scale study.

Its parameters of quality are as follows:

  • Clarity . The question should be specific about the focus of your inquiry.
  • Complexity . It should not be self-obvious or primitively answered with a “yes” or “no” variant.
  • Focus . The question should match the size and type of your academic assignment.
  • Conciseness . It should be brief and understandable.
  • Debatability . There should be more than one potential answer to the question.

😺 Research Question Examples: Good & Not So Good

Here are some examples to illustrate what we mean by quality criteria and how you can ensure that your question meets them.

Lack of Clarity

The bad example is too general and does not clearly estimate what effect you want to analyze or what aspect of video gaming you're interested in. A much better variant is in the right column.

Look at some other research question examples that are clear enough:

  • Terrorism: what is it and how to counter it?
  • Sex trafficking: why do we have to address it?
  • Palliative care: what constitutes the best technique for technicians communication with patients and families?
  • How do vacuum cleaners work?
  • What does it mean to age well?

Lack of Focus

The bad example is not focused, as it doesn’t specify what benefits you want to identify and in what context the uniform is approached. A more effective variant is in the right column.

Look at some other research question examples that are focused enough:

  • How are biochemical conditions and brain activity linked to crime?
  • World wars and national conflicts: what were the reasons?
  • Why does crime exist in society?
  • Decolonization in Canada: what does decolonization mean?

The bad example is too simplistic and doesn’t focus on the aspects of help that dogs can give to their owners. A more effective variant is in the right column.

Look at some other research question examples that are complex enough:

  • How is resource scarcity impacting the chocolate industry?
  • What should the Brazilian government do about reducing Amazon’s deforestation?
  • Why is a collaborative approach vital during a pandemic?
  • What impact has COVID-19 had on the economy?
  • How to teach handwriting effectively?

Lack of Debatability

The problem of diabetes is well-known and doesn’t cause any doubts. So, you should add debatability to the discussed issue.

Look at some other research question examples that are debatable enough:

  • Online vs. print journalism: what is more beneficial?
  • Why will artificial intelligence not replace human in near future?
  • What are the differences between art and design?
  • Crime TV: how is criminality represented on television?

The question in the left column is too long and ambiguous, making the readers lose focus. You can shorten it without losing the essence.

Look at some other research question examples that are concise enough:

  • What is the best way to address obesity in the US?
  • Doctoral degree in nursing: why is it important?
  • What are the benefits of X-rays in medicine?
  • To what extent do emotions influence moral judgment?
  • Why did the Industrial Revolution happen in England?

👣 Steps to Generate Research Questions

Now, it’s time to get down from science to practice. Here is a tried-and-tested algorithm for killer research question generation.

  • Pick a topic . Once you get a writing assignment, it’s time to find an appropriate topic first . You can’t formulate a thesis statement or research question if you know nothing about your subject, so it's time to narrow your scope and find out as much as possible about the upcoming task.
  • Research the topic . After you’re brainstormed several topic options, you should do some research. This stage takes the guesswork out of the academic process, allowing you to discover what scholars and other respected people think about your subject.
  • Clarify who your audience is . Think about who will read your piece. Will it be the professor, your classmates, or the general audience consisting of laypersons? Ensure the research question sounds competent enough for a professor and understandable enough for laypeople.
  • Approach the subject critically . With a well-articulated topic at hand, you should start asking the "why's" and "how's" about it. Look at the subject as a kid; don't limit your curiosity. You're sure to arrive at some interesting topics to reveal the hidden sides of the chosen issue.
  • Evaluate the questions . Now that you have a couple of questions about your topic, evaluate them in terms of research value. Are all of them clear and focused? Will answering all of them take time and research, or is the answer already on the surface? By assessing each option you’ve formulated, you’re sure to choose one leader and use it as your main research question for the scientific study.

Thank you for reading this article! If you need to quickly formulate a thesis statement, consider using our free thesis maker .

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  1. Quantitative research process

  2. Quantitative Research Designs 📊🔍: Know Your Options #shorts #research

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  1. A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles

    INTRODUCTION. Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses.1,2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results.3,4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the ...

  2. 10 Research Question Examples to Guide your Research Project

    Here are a few options for qualitative, quantitative, and statistical research questions. Other interesting articles If you want to know more about the research process, methodology, research bias, or statistics, make sure to check out some of our other articles with explanations and examples. Methodology Sampling methods Simple random sampling

  3. Quantitative Research Essay Examples

    1 hour! a 100% original paper Quantitative Research Essay Examples A quantitative research essay analyzes numerical data in the form of trends, opinions, or efficiency results. This academic writing genre requires you to generalize the figures across a broad group of people and make a relevant conclusion.

  4. Writing Strong Research Questions

    You can follow these steps to develop a strong research question: Choose your topic Do some preliminary reading about the current state of the field Narrow your focus to a specific niche Identify the research problem that you will address The way you frame your question depends on what your research aims to achieve.

  5. What Is Quantitative Research?

    Knowledge Base Methodology What Is Quantitative Research? | Definition, Uses & Methods What Is Quantitative Research? | Definition, Uses & Methods Published on June 12, 2020 by Pritha Bhandari . Revised on June 22, 2023. Quantitative research is the process of collecting and analyzing numerical data.

  6. How to Write Quantitative Research Questions: Types With Examples

    1. Select the Type of Quantitative Question The first step is to determine which type of quantitative question you want to add to your study. There are three types of quantitative questions: Descriptive Comparative Relationship-based This will help you choose the correct words and phrases while constructing the question.

  7. How to structure quantitative research questions

    There are six steps required to construct a descriptive research question: (1) choose your starting phrase; (2) identify and name the dependent variable; (3) identify the group (s) you are interested in; (4) decide whether dependent variable or group (s) should be included first, last or in two parts; (5) include any words that provide greater c...

  8. Quantitative Methods

    Quantitative research focuses on numeric and unchanging data and detailed, convergent reasoning rather than divergent reasoning [i.e., the generation of a variety of ideas about a research problem in a spontaneous, free-flowing manner]. Its main characteristics are: The data is usually gathered using structured research instruments.

  9. How to Write a Good Research Question (w/ Examples)

    It can be difficult to come up with a good research question, but there are a few steps you can follow to make it a bit easier. 1. Start with an interesting and relevant topic. Choose a research topic that is interesting but also relevant and aligned with your own country's culture or your university's capabilities.

  10. What Is Quantitative Research?

    Quantitative research is the opposite of qualitative research, which involves collecting and analysing non-numerical data (e.g. text, video, or audio). Quantitative research is widely used in the natural and social sciences: biology, chemistry, psychology, economics, sociology, marketing, etc. Quantitative research question examples.

  11. Formulating Your Research Question (RQ)

    Formulating Your Research Question (RQ) In an effort to make our handouts more accessible, we have begun converting our PDF handouts to web pages. In a research paper, the emphasis is on generating a unique question and then synthesizing diverse sources into a coherent essay that supports your argument about the topic.

  12. How to Write a Research Question: Types and Examples

    Choose a broad topic, such as "learner support" or "social media influence" for your study. Select topics of interest to make research more enjoyable and stay motivated. Preliminary research. The goal is to refine and focus your research question. The following strategies can help: Skim various scholarly articles.

  13. PDF Strategies for Essay Writing

    with a strong analytical question that you will try to answer in your essay. Your answer to that question will be your essay's thesis. You may have many questions as you consider a source or set of sources, but not all of your questions will form the basis of a strong essay. For example, your initial questions

  14. 4.3 Quantitative research questions

    Quantitative descriptive questions. The type of research you are conducting will impact the research question that you ask. Probably the easiest questions to think of are quantitative descriptive questions. For example, "What is the average student debt load of MSW students?" is a descriptive question—and an important one.

  15. (PDF) Writing Research Questions in a Quantitative Research: A

    Writing Research Questions in a Quantitative Research: A Simplified Version In book: Writing Research Questions in a Quantitative Research Publisher: WORLD EDUCATION CONNECT...

  16. Quantitative Research Essays: Examples, Topics, & Outlines

    Qualitative and Quantitative Research Methods. PAGES 2 WORDS 787. measurements that can be ascertained objectively. They employ statistical and mathematical data analysis; gathered through such techniques as polls, questionnaires, surveys or through manipulation of already existing data via computational techniques.

  17. 50+ Unique Quantitative Research Topics for Students

    Step 1: Choose the research topic. Remember, your research question will represent the type of quantitative research you will use in your dissertation. So, you should always consider choosing the type of research question quite carefully. It can be descriptive, comparative or relationship-based. If you already have a couple of plants and unique ...

  18. 500+ Quantitative Research Titles and Topics

    February 13, 2024 by Muhammad Hassan Table of Contents Quantitative research involves collecting and analyzing numerical data to identify patterns, trends, and relationships among variables.

  19. Qualitative vs. Quantitative Research

    Use quantitative research if you want to confirm or test something (a theory or hypothesis) Use qualitative research if you want to understand something (concepts, thoughts, experiences) For most research topics you can choose a qualitative, quantitative or mixed methods approach. Which type you choose depends on, among other things, whether ...

  20. 98 Quantitative Research Questions & Examples

    The ultimate list of questions for quantitative market research. Quantitative research question example: market analysis. Quantitative research questions for consumer behavior studies. Quantitative research question and answer: content strategy and analysis. As researchers, we know how powerful quantitative research data can be in helping ...

  21. What Are Quantitative Survey Questions? Types and Examples

    The rest of this article focuses on quantitative research, taking a closer look at quantitative survey question types and question formats/layouts. Back to table of contents . Types of quantitative survey questions - with examples . Quantitative questions come in many forms, each with different benefits depending on your market research objectives.

  22. Essay on Qualitative vs. Quantitative Research

    Number of words: 1320 Both qualitative and quantitative researches are valued in the research world and are often used together under a single project. This is despite the fact that they have significant differences in terms of their theoretical, epistemological, and methodological formations.

  23. Research Question Generator for Students

    Indicate your search term or title. Stipulate the subject or academic area. Press "Generate questions". Choose a suitable research question from the generated list. As you can see, this is the best research question generator requiring minimal input for smart question formulation. Try it out to see how simple the process is.

  24. Essay on Quantitative Research

    The essay will examine the application of qualitative, quantitative and mixed research methods in journals, assess their usefulness and present the results of the analysis. An examination of research methods and research design will identify trends in research methodologies employed in journals and try to explain the reason. 2019 Words. 9 Pages.

  25. An integrated fuzzy-rough multi-criteria group decision-making model

    The increase in the number of studies focusing on geoheritage, geoconservation, geoparks, and geotourism around the world has brought about the problem of revealing the value of geosites as a resource. Therefore, the quantitative values and usage patterns of geoheritage resources need to be determined. In this context, the current research uses fuzzy-rough MCGDM (multi-criteria group decision ...