quantitative research examples dissertation

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Listed below are some of the best examples of research projects and dissertations from undergraduate and taught postgraduate students at the University of Leeds We have not been able to gather examples from all schools. The module requirements for research projects may have changed since these examples were written. Refer to your module guidelines to make sure that you address all of the current assessment criteria. Some of the examples below are only available to access on campus.

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Quantitative research

In this section on Quantitative Research  you can find out about:

You might also want to consult our other sections on  Planning your research ,  Qualitative research , and  Writing up research , and check out the Additional resources .

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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 .

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.

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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Qualitative, quantitative and mixed methods dissertations

What are they and which one should i choose.

In the sections that follow, we briefly describe the main characteristics of qualitative, quantitative and mixed methods dissertations. Rather than being exhaustive, the main goal is to highlight what these types of research are and what they involve. Whilst you read through each section, try and think about your own dissertation, and whether you think that one of these types of dissertation might be right for you. After reading about these three types of dissertation, we highlight some of the academic, personal and practical reasons why you may choose to take on one type over another.

• Types of dissertation: Qualitative, quantitative and mixed methods dissertations
• Choosing between types: Academic, personal and practical justifications

Types of dissertation

Whilst we describe the main characteristics of qualitative, quantitative and mixed methods dissertations, the Lærd Dissertation site currently focuses on helping guide you through quantitative dissertations , whether you are a student of the social sciences, psychology, education or business, or are studying medical or biological sciences, sports science, or another science-based degree. Nonetheless, you may still find our introductions to qualitative dissertations and mixed methods dissertations useful, if only to decide whether these types of dissertation are for you. We discuss quantitative dissertations , qualitative dissertations and mixed methods dissertations in turn:

Quantitative dissertations

When we use the word quantitative to describe quantitative dissertations , we do not simply mean that the dissertation will draw on quantitative research methods or statistical analysis techniques . Quantitative research takes a particular approach to theory , answering research questions and/or hypotheses , setting up a research strategy , making conclusions from results , and so forth. Classic routes that you can follow include replication-based studies , theory-driven research and data-driven dissertations . However, irrespective of the particular route that you adopt when taking on a quantitative dissertation, there are a number of core characteristics to quantitative dissertations:

They typically attempt to build on and/or test theories , whether adopting an original approach or an approach based on some kind of replication or extension .

They answer quantitative research questions and/or research (or null ) hypotheses .

They are mainly underpinned by positivist or post-positivist research paradigms .

They draw on one of four broad quantitative research designs (i.e., descriptive , experimental , quasi-experimental or relationship-based research designs).

They try to use probability sampling techniques , with the goal of making generalisations from the sample being studied to a wider population , although often end up applying non-probability sampling techniques .

They use research methods that generate quantitative data (e.g., data sets , laboratory-based methods , questionnaires/surveys , structured interviews , structured observation , etc.).

They draw heavily on statistical analysis techniques to examine the data collected, whether descriptive or inferential in nature.

They assess the quality of their findings in terms of their reliability , internal and external validity , and construct validity .

They report their findings using statements , data , tables and graphs that address each research question and/or hypothesis.

They make conclusions in line with the findings , research questions and/or hypotheses , and theories discussed in order to test and/or expand on existing theories, or providing insight for future theories.

If you choose to take on a quantitative dissertation , go to the Quantitative Dissertations part of Lærd Dissertation now. You will learn more about the characteristics of quantitative dissertations, as well as being able to choose between the three classic routes that are pursued in quantitative research: replication-based studies , theory-driven research and data-driven dissertations . Upon choosing your route, the Quantitative Dissertations part of Lærd Dissertation will help guide you through these routes, from topic idea to completed dissertation, as well as showing you how to write up quantitative dissertations.

Qualitative dissertations

Qualitative dissertations , like qualitative research in general, are often associated with qualitative research methods such as unstructured interviews, focus groups and participant observation. Whilst they do use a set of research methods that are not used in quantitative dissertations, qualitative research is much more than a choice between research methods. Qualitative research takes a particular approach towards the research process , the setting of research questions , the development and use of theory , the choice of research strategy , the way that findings are presented and discussed, and so forth. Overall, qualitative dissertations will be very different in approach, depending on the particular route that you adopt (e.g., case study research compared to ethnographies). Classic routes that you can follow include autoethnographies , case study research , ethnographies , grounded theory , narrative research and phenomenological research . However, irrespective of the route that you choose to follow, there are a number of broad characteristics to qualitative dissertations:

They follow an emergent design , meaning that the research process , and sometimes even the qualitative research questions that you tackle, often evolve during the dissertation process.

They use theory in a variety of ways - sometimes drawing on theory to help the research process; on other occasions, using theory to develop new theoretical insights ; sometimes both - but the goal is infrequently to test a particular theory from the outset.

They can be underpinned by one of a number of research paradigms (e.g., interpretivism , constructivism , critical theory , amongst many other research paradigms).

They follow research designs that heavily influence the choices you make throughout the research process, as well as the analysis and discussion of 'findings' (i.e., such research designs differ considerably depending on the route that is being followed, whether an autoethnography , case study research , ethnography , grounded theory , narrative research , phenomenological research , etc.).

They try to use theoretical sampling - a group of non-probability sampling techniques - with the goal of studying cases (i.e., people or organisations) that are most appropriate to answering their research questions.

They study people in-the-field (i.e., in natural settings ), often using multiple research methods , each of which generate qualitative data (e.g., unstructured interviews , focus groups , participant observation , etc.).

They interpret the qualitative data through the eyes and biases of the researcher , going back-and-forth through the data (i.e., an inductive process ) to identify themes or abstractions that build a holistic/gestalt picture of what is being studied.

They assess the quality of their findings in terms of their dependability , confirmability , conformability and transferability .

They present (and discuss ) their findings through personal accounts , case studies , narratives , and other means that identify themes or abstracts , processes , observations and contradictions , which help to address their research questions.

They discuss the theoretical insights arising from the findings in light of the research questions, from which tentative conclusions are made.

If you choose to take on a qualitative dissertation , you will be able to learn a little about appropriate research methods and sampling techniques in the Fundamentals section of Lærd Dissertation. However, we have not yet launched a dedicated section to qualitative dissertations within Lærd Dissertation. If this is something that you would like us to do sooner than later, please leave feedback .

Mixed methods dissertations

Mixed methods dissertations combine qualitative and quantitative approaches to research. Whilst they are increasingly used and have gained greater legitimacy, much less has been written about their components parts. There are a number of reasons why mixed methods dissertations are used, including the feeling that a research question can be better addressed by:

Collecting qualitative and quantitative data , and then analysing or interpreting that data, whether separately or by mixing it.

Conducting more than one research phase ; perhaps conducting qualitative research to explore an issue and uncover major themes, before using quantitative research to measure the relationships between the themes.

One of the problems (or challenges) of mixed methods dissertations is that qualitative and quantitative research, as you will have seen from the two previous sections, are very different in approach. In many respects, they are opposing approaches to research. Therefore, when taking on a mixed methods dissertation, you need to think particularly carefully about the goals of your research, and whether the qualitative or quantitative components (a) are more important in philosophical, theoretical and practical terms, and (b) should be combined or kept separate.

Again, as with qualitative dissertations, we have yet to launch a dedicated section of Lærd Dissertation to mixed methods dissertations . However, you will be able to learn about many of the quantitative aspects of doing a mixed methods dissertation in the Quantitative Dissertations part of Lærd Dissertation. You may even be able to follow this part of our site entirely if the only qualitative aspect of your mixed methods dissertation is the use of qualitative methods to help you explore an issue or uncover major themes, before performing quantitative research to examine such themes further. Nonetheless, if you would like to see a dedicated section to mixed methods dissertations sooner than later, please leave feedback .

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• Dissertation Topics

Quantitative research is an organised way of studying things using surveys or experiments to count and analyse numbers, focusing on testing theories based on facts and logical thinking. Quantitative research aims to gather and analyse numerical data to test hypotheses, make predictions, or explore relationships between variables. Thus, students must look for meaningful quantitative research titles and topics to achieve success in their dissertations.

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Education quantitative research topics for students.

Topic 1.  Utilising Artificial Intelligence in Adaptive Learning Platforms: Enhancing Student Engagement and Academic Performance

Topic 2.  Online Learning Analytics: Quantifying Student Learning Patterns and Predicting Success

Topic 3. Exploring the Impact of Gamified Learning Environments on Mathematics Achievement in Elementary Schools

Topic 4. Personalized Learning Pathways: A Quantitative Analysis of Student Outcomes in Higher Education

Topic 5. Digital Literacy in Education: Assessing the Effects of Technology Integration on Literacy Skills Development

Topic 6. Examining the Relationship Between Classroom Environment and Student Motivation: A Multilevel Analysis

Topic 7. Evaluating the Effectiveness of Flipped Classroom Models in STEM Education: A Longitudinal Study

Topic 8. Evaluating the Effects of Peer Tutoring Programs on Academic Achievement: A Meta-analysis

Topic 9. The Influence of Teacher-Student Relationships on Academic Success: A Quantitative Study

Topic 10. Online Education During the COVID-19 Pandemic: Analyzing Student Engagement and Learning Outcomes

Healthcare Quantitative Research Titles

Topic 11. Enhancing Remote Patient Monitoring: A Quantitative Analysis of Wearable Health Technology in Chronic Disease Management

Topic 12. Exploring the Impact of Artificial Intelligence in Diagnostic Radiology: Quantifying Accuracy and Efficiency

Topic 13. Telehealth in Mental Health Care: Analyzing Patient Satisfaction and Treatment Outcomes

Topic 14. Remote Consultations in Dermatology: Assessing Effectiveness and Patient Experience

Topic 15. Addressing Health Disparities in Telemedicine: A Quantitative Study on Access and Equity

Topic 16. Quantifying the Benefits of Virtual Reality Therapy in Pain Management: A Comparative Study

Topic 17. Harnessing Blockchain Technology in Healthcare: A Quantitative Evaluation of Data Security and Efficiency

Topic 18. The Role of Chatbots in Healthcare Communication: An Analysis of User Satisfaction and Interaction Patterns

Topic 19. Optimising Medication Management through Digital Health Platforms: A Quantitative Assessment of Adherence and Health Outcomes

Topic 20. Personalized Medicine and Genomic Testing: Assessing Patient Understanding and Decision-Making Processes

Business and Economics Quantitative Topics

Topic 21. Evaluating the Impact of E-commerce Platforms on Consumer Behavior: A Quantitative Analysis of Purchase Patterns

Topic 22. The Role of Social Media Marketing in Brand Engagement: A Quantitative Study of User Interaction Metrics

Topic 23. Quantifying the Effects of Corporate Social Responsibility on Brand Equity and Financial Performance

Topic 24. Exploring the Influence of Economic Factors on Entrepreneurial Intentions: A Cross-country Analysis

Topic 25. Analysing the Relationship Between Workplace Diversity and Organizational Performance: A Multilevel Study

Topic 26. The Impact of Supply Chain Disruptions on Firm Performance: A Quantitative Analysis of Financial Indicators

Topic 27. Assessing the Effects of Financial Education Programs on Financial Literacy Levels: A Longitudinal Study

Topic 28. Quantifying the Benefits of Employee Training and Development Programs: A Comparative Analysis

Topic 29. Exploring the Role of Fintech Innovations in Financial Inclusion: A Cross-sectional Study

Topic 30. Analysing the Effects of Corporate Governance Mechanisms on Firm Value: A Panel Data Analysis

Psychology and Mental Health Examples of Quantitative Research Titles

Topic 31. Quantifying the Impact of Mindfulness-based Interventions on Stress Reduction and Psychological Well-being

Topic 32. Exploring the Relationship Between Social Media Use and Mental Health Outcomes Among Adolescents

Topic 33. The Influence of Parenting Styles on Adolescent Emotional Regulation: A Longitudinal Study

Topic 34. Assessing the Effects of Peer Support Programs on Mental Health Recovery: A Randomized Controlled Trial

Topic 35. Quantifying the Benefits of Exercise on Depression Management: A Meta-analysis

Topic 36. Understanding the Relationship Between Personality Traits and Job Satisfaction: A Cross-sectional Study

Topic 37. Analysing the Effects of Trauma Exposure on Psychological Distress and Resilience Among Veterans

Topic 38. Exploring the Role of Sleep Quality in Cognitive Functioning and Academic Performance

Topic 39. Quantitative Assessment of the Effects of Smartphone Addiction on Mental Health Outcomes

Topic 40. Evaluating the Relationship Between Childhood Adversity and Adult Mental Health Disorders: A Population-based Study

Environmental Science Research Titles Examples

Topic 41. Assessing the Impact of Climate Change on Biodiversity Loss: A Quantitative Analysis of Species Extinction Rates

Topic 42. Exploring the Relationship Between Air Pollution Exposure and Respiratory Health Outcomes in Urban Areas

Topic 43. The Influence of Urban Green Spaces on Mental Health and Well-being: A Geographic Information System (GIS) Analysis

Topic 44. Quantifying the Effects of Plastic Pollution on Marine Ecosystems: A Meta-analysis of Research Findings

Topic 45. Analysing the Relationship Between Land Use Change and Water Quality Degradation in Watersheds

Topic 46. Understanding the Effects of Deforestation on Carbon Sequestration and Climate Change Mitigation

Topic 47. Evaluating the Efficacy of Renewable Energy Policies in Reducing Greenhouse Gas Emissions: A Comparative Study

Topic 48. Quantifying the Benefits of Sustainable Agriculture Practices on Soil Health and Crop Yields

Topic 49. Examining the Impact of Urbanization on Heat Island Effects: A Remote Sensing Analysis

Topic 50. Analysing the Effectiveness of Carbon Curbing Strategies Proposed at COP28: A Quantitative Assessment of Environmental Impact and Policy Implementation

Sociology and Social Sciences Quantitative Research Topics for Students

Topic 51. Evaluating the Impact of Social Media Use on Mental Health Among Adolescents: A Longitudinal Study

Topic 52. Quantifying the Effects of Income Inequality on Social Mobility and Economic Prosperity: A Cross-national Analysis

Topic 53. Exploring the Relationship Between Climate Change Awareness and Pro-environmental Behaviors: A Multilevel Analysis

Topic 54. Analysing the Correlation Between Workplace Diversity and Organizational Performance: A Meta-analysis

Topic 55. Assessing the Effects of Community Policing Strategies on Crime Reduction: A Comparative Study

Topic 56. Quantitative Assessment of Gender Stereotypes in STEM Education: A Longitudinal Analysis

Topic 57. Examining the Influence of Social Support Networks on Resilience Among Refugee Populations: A Cross-cultural Study

Topic 58. Assessing the Impact of Universal Basic Income on Poverty Alleviation and Social Welfare: A Comparative Analysis

Topic 59. Quantifying the Benefits of Cultural Diversity in Urban Neighborhoods: A Spatial Analysis

Topic 60. Exploring the Relationship Between Social Capital and Mental Health Outcomes: A Population-based Study

Technology and Computing Quantitative Research Titles Examples

Topic 61. Analysing the Effects of Artificial Intelligence on Job Market Dynamics: A Forecasting Study

Topic 62. Quantifying the Benefits of Blockchain Technology in Supply Chain Management: A Case Study Approach

Topic 63. Evaluating the Impact of Cybersecurity Threats on Financial Institutions: A Risk Assessment Analysis

Topic 64. Examining the Relationship Between Social Media Usage and Mental Health: A Longitudinal Study

Topic 65. Quantitative Analysis of Online Privacy Concerns and User Behavior: A Cross-sectional Survey

Topic 66. Assessing the Efficacy of Augmented Reality Applications in Education: A Randomized Controlled Trial

Topic 67. Exploring the Influence of Virtual Reality Gaming on Spatial Skills Development: A Longitudinal Study

Topic 68. Quantifying the Effects of Remote Work on Employee Productivity and Job Satisfaction: A Comparative Analysis

Topic 69. Evaluating the Relationship Between Technology Adoption and Firm Performance: A Panel Data Analysis

Topic 70. Analysing the Correlation Between Digital Literacy and Academic Achievement: A Cross-national Study

Political Science Research Title Examples Quantitative

Topic 71. Examining the Effects of Social Media Algorithms on Political Polarization: A Network Analysis

Topic 72. Quantifying the Impact of Electoral College Reform on Democratic Representation: A Simulation Study

Topic 73. Assessing the Efficacy of Election Campaign Strategies on Voter Turnout: A Comparative Analysis

Topic 74. Exploring the Relationship Between Political Ideology and Environmental Policy Support: A Cross-national Survey

Topic 75. Evaluating the Effects of Immigration Policies on Social Cohesion and Integration: A Longitudinal Study

Topic 76. Quantitative Analysis of Government Response to Public Health Crises: A Comparative Study

Topic 77. Analysing the Correlation Between Foreign Aid Allocation and Diplomatic Relations: A Time-series Analysis

Topic 78. Examining the Influence of Lobbying Expenditures on Legislative Decision-making: A Regression Analysis

Topic 79. Quantifying the Effects of Media Bias on Public Opinion Formation: A Survey Experiment

Topic 80. Assessing the Impact of Campaign Finance Regulations on Political Campaigns: A Policy Evaluation Study

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Engineering and Technology Quantitative Research Examples Title

Topic 81. Exploring the Impact of Artificial Intelligence on Sustainable Urban Development: A Smart Cities Case Study

Topic 82. Quantifying the Effects of Renewable Energy Integration on Power Grid Stability: A System Dynamics Analysis

Topic 83. Analysing the Relationship Between Transportation Infrastructure Investment and Economic Growth: A Panel Data Analysis

Topic 84. Evaluating the Efficacy of Green Building Technologies in Mitigating Climate Change: A Life Cycle Assessment

Topic 85. Quantitative Assessment of Urban Air Quality Management Strategies: A Multi-criteria Decision Analysis

Topic 86. Examining the Effects of Smart Transportation Systems on Traffic Congestion: A Simulation Modeling Approach

Topic 87. Quantifying the Benefits of Digital Twins Technology in Manufacturing: A Cost-benefit Analysis

Topic 88. Analysing the Correlation Between IoT Adoption and Energy Efficiency in Smart Buildings: A Cross-sectional Study

Topic 89. Evaluating the Impact of 5G Technology Deployment on Economic Productivity: A Time-series Analysis

Topic 90. Exploring the Relationship Between Cybersecurity Investments and Firm Performance: A Regression Analysis

Medicine and Healthcare Quantitative Topics

Topic 91. Assessing the Efficacy of Telehealth Interventions in Chronic Disease Management: A Randomized Controlled Trial

Topic 92. Quantifying the Effects of Lifestyle Interventions on Type 2 Diabetes Prevention: A Population-based Study

Topic 93. Evaluating the Relationship Between Healthcare Access and Health Disparities: A Spatial Analysis

Topic 94. Examining the Impact of Precision Medicine on Cancer Treatment Outcomes: A Longitudinal Study

Topic 95. Quantitative Assessment of Patient Satisfaction with Virtual Health Services: A Cross-sectional Survey

Topic 96. Analysing the Correlation Between Mental Health Disorders and Substance Use: A National Survey

Topic 97. Exploring the Influence of Social Determinants of Health on Healthcare Utilization: A Multilevel Analysis

Topic 98. Quantifying the Benefits of Integrative Health Approaches in Pain Management: A Meta-analysis

Topic 99. Evaluating the Relationship Between Physician Burnout and Patient Safety: A Longitudinal Study

Topic 100. Assessing the Impact of Healthcare Policies on Maternal and Child Health Outcomes: A Comparative Analysis

Topic 101. Analysing the Impact of Climate Change on Infectious Disease Transmission: A Quantitative Analysis

Quantitative Research Titles Examples for Highschool Students

Topic 102. The Impact of Study Habits on Academic Performance: A Quantitative Analysis

Topic 103. Social Media Usage and Its Effects on Teenage Well-being: A Quantitative Study

Topic 104. The Relationship Between Sleep Patterns and Grade Point Average: A Quantitative Investigation

Topic 105. Analysing the Effects of Extracurricular Activities on Student Engagement and Achievement

Topic 106. Quantifying the Influence of Parental Involvement on High School Students' Academic Success

Quantitative Research Topics in Fashion

Topic 107. Analysing The Impact Of Digital Marketing Strategies On The Sales Of Sustainable Fashion Brands

Topic 108. Examining Consumer Willingness To Pay For Ethical Fashion: A Comparative Study Between Urban And Rural Areas in the UK

Topic 109. Evaluating the Effect Of Fashion Influencers On Instagram On Brand Perception And Purchase Intentions

Topic 110. Quantifying The Relationship Between Fashion Show Attendance And Luxury Brand Sales Growth

Topic 111. Evaluating The Role Of Augmented Reality In Enhancing Online Shopping Experience For Fashion Retailers

Topic 112. Analysing Price Sensitivity And Purchasing Behavior in the Fast Fashion Industry

Topic 113. Examining Seasonal Variations In Consumer Spending On Outdoor Apparel

Topic 114. Analysing Gender Differences In Online Shopping Behavior For Fashion Items

Topic 115. Assessing the Influence Of Celebrity Endorsements on Athletic Wear Sales

Topic 116. Analysing the Impact Of COVID-19 On Consumer Preferences For Loungewear And Casual Clothing

Accounting and Finance Quantitative Research Examples Title

Topic 117. Examining The Impact Of Financial Ratios On The Stock Price Movements Of Technology Companies

Topic 118. Analysing The Relationship Between Corporate Governance And Financial Performance In The Banking Sector

Topic 119. Exploring The Effect Of Interest Rate Changes On The Profitability Of Regional Banks

Topic 120. Evaluating The Role Of Financial Leverage In Predicting Bankruptcy Among Small And Medium Enterprises

Topic 121. Assessing The Impact Of Dividend Policy On Stock Market Returns In Emerging Markets

Topic 122. Examining The Effects Of Exchange Rate Fluctuations On The Financial Performance Of Multinational Corporations

Topic 123. Analysing The Influence Of Credit Risk On Lending Practices In Commercial Banks

Topic 124. Exploring The Relationship Between Inflation And Investment Returns In The Real Estate Sector

Topic 125. Evaluating The Impact Of Mergers And Acquisitions On Shareholder Value In The Pharmaceutical Industry

Topic 126. Assessing The Financial Performance Of Environmentally Sustainable Companies In The Energy Sector

Project Management Quantitative Research Titles

Topic 127. Examining The Impact Of Project Management Methodologies On Project Success Rates In The IT Sector

Topic 128. Analysing The Relationship Between Project Leadership Styles And Team Performance In Construction Projects

Topic 129. Exploring The Effect Of Risk Management Practices On Project Outcomes In The Pharmaceutical Industry

Topic 130. Evaluating The Influence Of Stakeholder Engagement On The Success Of Large-Scale Infrastructure Projects

Topic 131. Assessing The Role Of Project Scheduling Tools In Meeting Deadlines In Software Development Projects

Topic 132. Examining The Impact Of Agile Project Management On Product Development Cycles In The Tech Industry

Topic 133. Analysing The Relationship Between Resource Allocation And Project Efficiency In Renewable Energy Projects

Topic 134. Exploring The Effects Of Project Communication Strategies On Team Collaboration In Remote Work Environments

Topic 135. Evaluating The Impact Of Budget Management Techniques On Financial Performance Of Construction Projects

Topic 136. Assessing The Role Of Quality Assurance Processes In Reducing Project Defects In Manufacturing Projects

Topic 137. Examining The Effects Of Change Management Practices On Employee Adaptation In Organizational Projects

Topic 138. Analysing The Relationship Between Project Complexity And Delivery Time In Aerospace Projects

Topic 139. Exploring The Influence Of Cultural Diversity On Project Team Dynamics In International Projects

Topic 140. Evaluating The Impact Of Project Portfolio Management On Strategic Alignment In Financial Services Firms

Marketing Quantitative Research Topics for Students

Topic 141. Examining The Impact Of Social Media Advertising On Consumer Purchase Intentions In The Fashion Industry

Topic 142. Analysing The Relationship Between Brand Loyalty And Customer Retention In The Retail Sector

Topic 143. Exploring The Effect Of Email Marketing Campaigns On Conversion Rates In E-Commerce Businesses

Topic 144. Evaluating The Influence Of Celebrity Endorsements On Brand Perception In The Beauty Industry

Topic 145. Assessing The Role Of Price Promotions On Sales Volume In The Grocery Sector

Topic 146. Examining The Impact Of Influencer Marketing On Brand Awareness Among Millennials

Topic 147. Analysing The Relationship Between Content Marketing Strategies And Lead Generation In B2B Companies

Topic 148. Exploring The Effects Of Mobile Marketing On Consumer Engagement In The Travel Industry

Topic 149. Evaluating The Impact Of Customer Reviews On Online Purchase Decisions In The Electronics Market

Topic 150. Assessing The Role Of Loyalty Programs In Enhancing Customer Lifetime Value In The Hospitality Industry

Topic 151. Examining The Effects Of Product Packaging On Consumer Buying Behavior In The Food And Beverage Sector

Topic 152. Analysing The Relationship Between Digital Marketing Spend And Revenue Growth In Startups

Topic 153. Exploring The Influence Of Cultural Differences On International Marketing Strategies In The Automotive Industry

Topic 154. Evaluating The Impact Of Personalization In Email Marketing On Open And Click-Through Rates

Topic 155. Assessing The Effectiveness Of Video Marketing On Brand Engagement In The Fitness Industry

Social Media Quantitative Research Titles

Topic 156. Examining The Impact Of Social Media Influencers On Consumer Purchase Decisions In The Fashion Industry

Topic 157. Analysing The Relationship Between Social Media Engagement And Brand Loyalty In The Beverage Sector

Topic 158. Exploring The Effect Of Social Media Advertising On Brand Awareness Among Gen Z Consumers

Topic 159. Evaluating The Influence Of Social Media Contests On User Engagement In The Cosmetics Industry

Topic 160. Assessing The Role Of User-Generated Content In Shaping Brand Perception On Instagram

Topic 161. Examining The Impact Of Social Media Reviews On Product Sales In The Electronics Market

Topic 162. Analysing The Relationship Between Social Media Activity And Customer Retention In Online Retail

Topic 163. Exploring The Effects Of Social Media Campaigns On Political Participation Among Young Adults

Topic 164. Evaluating The Impact Of Facebook Ads On Small Business Growth In Urban Areas

Topic 165. Assessing The Role Of Social Media Sentiment Analysis In Predicting Stock Market Movements

Topic 166. Examining The Effects Of Social Media Influencer Collaborations On Brand Equity In The Fitness Industry

Topic 167. Analysing The Relationship Between Social Media Content Strategies And Audience Growth For Nonprofits

Topic 168. Exploring The Influence Of Social Media Trends On Consumer Behavior In The Tech Industry

Topic 169. Evaluating The Impact Of Social Media Customer Service Interactions On Brand Trust

Topic 170. Assessing The Effectiveness Of Social Media Crisis Management On Brand Reputation

Art Quantitative Topics

Topic 171. Examining The Impact Of Art Education Programs On Student Academic Achievement In Elementary Schools

Topic 172. Analysing The Relationship Between Museum Attendance And Public Art Funding In Urban Areas

Topic 173. Exploring The Effect Of Digital Art Platforms On Traditional Art Sales

Topic 174. Evaluating The Influence Of Art Therapy On Mental Health Outcomes Among Veterans

Topic 175. Assessing The Role Of Public Art Installations In Community Engagement And Social Cohesion

Topic 176. Examining The Impact Of Social Media On The Popularity And Sales Of Emerging Artists

Topic 177. Analysing The Relationship Between Art Market Trends And Economic Indicators

Topic 178. Exploring The Effects Of Art Gallery Exhibitions On Local Business Revenues

Topic 179. Evaluating The Impact Of Government Grants On The Sustainability Of Nonprofit Art Organizations

Topic 180. Assessing The Role Of Art Competitions In Promoting Artistic Talent Among High School Students

Topic 181. Examining The Effects Of Virtual Reality Art Experiences On Audience Engagement

Topic 182. Analysing The Relationship Between Art Collector Demographics And Art Investment Strategies

Topic 183. Exploring The Influence Of Cultural Festivals On The Preservation Of Traditional Art Forms

Topic 184. Evaluating The Impact Of Corporate Art Collections On Employee Creativity And Productivity

Topic 185. Assessing The Effectiveness Of Online Art Courses On Skill Development In Amateur Artists

Data Science Research Titles Examples

Topic 186. Examining the Impact of Machine Learning Algorithms on Predictive Accuracy in Healthcare Diagnostics

Topic 187. Analysing the Relationship Between Data Quality and Business Performance in Financial Institutions

Topic 188. Exploring the Effectiveness of Natural Language Processing Techniques in Sentiment Analysis of Social Media Data

Topic 189. Evaluating the Influence of Feature Selection Methods on Model Performance in Credit Risk Prediction

Topic 190. Examining the Impact of Data Preprocessing Techniques on Anomaly Detection in Network Security.

Topic 191. Analysing the Relationship Between Data Imputation Methods and Predictive Accuracy in Customer Churn Analysis.

Topic 192. Exploring the Effect of Dimensionality Reduction Techniques on Clustering Performance in Genomic Data Analysis

Topic 193. Evaluating the Influence of Sampling Methods on Model Generalization in Fraud Detection

Topic 194. Assessing the Role of Ensemble Learning Approaches in Forecasting Stock Market Trends.

Topic 195. Examining the Impact of Explainable AI Techniques on Model Interpretability in Predictive Maintenance

Topic 196. Analysing the Relationship Between Data Visualization Techniques and Decision-Making in Business Intelligence

Topic 197. Exploring the Effectiveness of Time Series Forecasting Models in Demand Prediction for E-commerce

Topic 198. Evaluating the Influence of Feature Engineering Strategies on Model Performance in Customer Segmentation

Topic 199. Assessing the Role of Reinforcement Learning Algorithms in Optimizing Supply Chain Management

Topic 200. Assessing the Role of Deep Learning Models in Image Recognition for Autonomous Vehicles

Quantitative Research Topics For Nursing Students

Topic 201. Analysing the Impact of Nurse-Patient Ratios on Patient Outcomes: A Quantitative Study

Topic 202. Evaluating the Effectiveness of Hand Hygiene Protocols in Reducing Hospital-Acquired Infections: A Systematic Review

Topic 203. Assessing the Relationship Between Nurse Burnout and Patient Satisfaction Levels: A Case Study

Topic 204. Exploring the Role of Telehealth in Managing Chronic Diseases: Challenges and Opportunities

Topic 205. Examining the Effect of Shift Length on Nurse Performance and Patient Safety: A Meta-Analysis

Topic 206. Analysing Patient Recovery Time in Post-Operative Care with Nursing Interventions: A Quantitative Study

Topic 207. Evaluating the Outcomes of Early vs. Late Ambulation After Surgery: A Systematic Review

Topic 208. Assessing Pain Management Techniques in Pediatric Patients: A Case Study

Topic 209. Exploring the Effectiveness of Simulation-Based Training on Nursing Students’ Clinical Skills: A Quantitative Study

Topic 210. Examining the Impact of Evidence-Based Practice on Patient Care Outcomes: A Meta-Analysis

Topic 211. Analysing Patient Outcomes in Magnet vs. Non-Magnet Hospitals: A Quantitative Study

Topic 212. Evaluating the Prevalence of Falls in Elderly Patients in Nursing Homes: Challenges and Opportunities

Topic 213. Assessing the Influence of Continuing Education on Nursing Competency and Patient Care: A Systematic Review

Topic 214. Exploring Nurse-Led Educational Programs on Diabetic Patient Outcomes: A Case Study

Topic 215. Examining Patient Education’s Impact on Medication Adherence in Chronic Illnesses: A Quantitative Study

Topic 216. Analysing Recovery Rates in Patients Receiving Traditional vs. Holistic Nursing Care: A Meta-Analysis

Topic 217. Evaluating Anxiety and Depression Prevalence in Oncology Nurses: Challenges and Opportunities

Topic 218. Assessing Nutrition Management’s Effect on Healing Pressure Ulcers: A Case Study

Topic 219. Exploring Patient Satisfaction in Telehealth vs. In-Person Consultations: A Quantitative Study

Topic 220. Examining the Relationship Between Work Environment and Nurse Job Satisfaction: A Cross-Sectional Study

Quantitative Research Topics For High School Students

Topic 221. Analysing the Relationship Between Study Habits and Academic Performance: A Quantitative Study

Topic 222. Evaluating the Impact of Social Media Usage on Teenagers' Sleep Patterns: A Case Study

Topic 223. Assessing the Correlation Between Physical Activity and Mental Health in Adolescents: A Systematic Review

Topic 224. Exploring the Effect of Part-Time Jobs on High School Students' Academic Success: Challenges and Opportunities

Topic 225. Examining the Influence of Classroom Environment on Student Engagement: A Meta-Analysis

Topic 226. Analysing the Impact of Extracurricular Activities on High School Students' Grades: A Quantitative Study

Topic 227. Evaluating the Effects of Nutrition on Academic Performance in High School Students: A Qualitative Study

Topic 228. Assessing the Relationship Between Screen Time and Academic Achievement: A Systematic Review

Topic 229. Exploring the Impact of School Start Times on Student Alertness and Performance: Challenges and Opportunities

Topic 230. Examining the Correlation Between Parental Involvement and Student Success: A Meta-Analysis

Topic 231. Analysing the Effects of Bullying on Student Academic Performance: A Quantitative Study

Topic 232. Evaluating the Relationship Between Homework Load and Student Stress Levels: A Case Study

Topic 233. Assessing the Impact of Technology Integration in Classrooms on Learning Outcomes: A Systematic Review

Topic 234. Exploring the Influence of Peer Pressure on High School Students' Academic Choices: Challenges and Opportunities

Topic 235. Examining the Relationship Between Sleep Duration and Academic Performance: A Quantitative Study

Topic 236. Analysing the Effect of Music on Studying Efficiency in High School Students: A Meta-Analysis

Topic 237. Evaluating the Impact of School Uniforms on Student Behavior and Academic Performance: A Qualitative Study

Topic 238. Assessing the Relationship Between Substance Use and Academic Achievement in High School Students: A Systematic Review

Topic 239. Exploring the Effects of Group Study vs. Individual Study on Academic Performance: Challenges and Opportunities

Topic 240. Examining the Influence of Socioeconomic Status on High School Graduation Rates: A Quantitative Study

Quantitative Research Topics For Humms Students

Topic 241. Analysing the Impact of Social Media on Teenagers' Mental Health: A Quantitative Study

Topic 242. Evaluating the Relationship Between Socioeconomic Status and Educational Attainment: A Systematic Review

Topic 243. Assessing the Effect of Peer Pressure on Academic Performance: A Case Study

Topic 244. Exploring the Influence of Family Dynamics on Adolescent Behavior: Challenges and Opportunities

Topic 245. Examining the Correlation Between Reading Habits and Academic Success: A Meta-Analysis

Topic 246. Analysing the Effects of Cultural Activities on Students' Social Skills: A Quantitative Study

Topic 247. Evaluating the Impact of Political Awareness on Civic Engagement Among Youth: A Qualitative Study

Topic 248. Assessing the Relationship Between Time Management Skills and Stress Levels in Students: A Systematic Review

Topic 249. Exploring the Influence of Mass Media on Public Opinion: Challenges and Opportunities

Topic 250. Examining the Effects of Urbanization on Community Cohesion: A Case Study

Topic 251. Analysing the Role of Extracurricular Activities in Developing Leadership Skills: A Quantitative Study

Topic 252. Evaluating the Impact of Educational Programs on Gender Equality Perceptions: A Qualitative Study

Topic 253. Assessing the Relationship Between School Environment and Student Motivation: A Systematic Review

Topic 254. Exploring the Influence of Historical Awareness on National Identity Among Students: Challenges and Opportunities

Topic 255. Examining the Effects of Social Media Exposure on Body Image Perception: A Meta-Analysis

Topic 256. Analysing the Relationship Between Volunteer Work and Empathy in Adolescents: A Quantitative Study

Topic 257. Evaluating the Impact of Bilingual Education on Cognitive Development: A Qualitative Study

Topic 258. Assessing the Influence of Teacher-Student Relationships on Academic Outcomes: A Systematic Review

Topic 259. Exploring the Effects of Economic Inequality on Social Mobility: Challenges and Opportunities

Topic 260. Examining the Relationship Between Media Consumption and Political Polarization: A Quantitative Study

Quantitative Research Topics For STEM Students

Topic 261. Analysing the Effectiveness of Renewable Energy Sources in Reducing Carbon Emissions: A Quantitative Study

Topic 262. Evaluating the Impact of Artificial Intelligence on Data Processing Efficiency: A Systematic Review

Topic 263. Assessing the Relationship Between Coding Skills and Problem-Solving Abilities in Students: A Case Study

Topic 264. Exploring the Influence of Robotics on Manufacturing Productivity: Challenges and Opportunities

Topic 265. Examining the Correlation Between Math Proficiency and Success in Science Subjects: A Meta-Analysis

Topic 266. Analysing the Effects of Climate Change on Biodiversity: A Quantitative Study

Topic 267. Evaluating the Efficiency of Different Algorithms in Machine Learning Applications: A Systematic Review

Topic 268. Assessing the Impact of Virtual Labs on Science Education Outcomes: A Case Study

Topic 269. Exploring the Role of Nanotechnology in Medical Diagnostics: Challenges and Opportunities

Topic 270. Examining the Effects of Cybersecurity Measures on Data Breach Incidents: A Meta-Analysis

Topic 271. Analysing the Relationship Between Internet Speed and Online Learning Effectiveness: A Quantitative Study

Topic 272. Evaluating the Impact of Biotechnology on Agricultural Productivity: A Qualitative Study

Topic 273. Assessing the Influence of STEM Outreach Programs on Student Interest in STEM Careers: A Systematic Review

Topic 274. Exploring the Effectiveness of Online vs. Traditional Classrooms in STEM Education: Challenges and Opportunities

Topic 275. Examining the Relationship Between Environmental Pollution and Public Health: A Meta-Analysis

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Methodology

• 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.

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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Streefkerk, R. (2023, June 22). Qualitative vs. Quantitative Research | Differences, Examples & Methods. Scribbr. Retrieved August 29, 2024, from https://www.scribbr.com/methodology/qualitative-quantitative-research/

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