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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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Edward barroga.
1 Department of General Education, Graduate School of Nursing Science, St. Luke’s International University, Tokyo, Japan.
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.
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.
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
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
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 .
Quantitative research questions | Quantitative research hypotheses |
---|---|
Descriptive research questions | Simple hypothesis |
Comparative research questions | Complex hypothesis |
Relationship research questions | Directional hypothesis |
Non-directional hypothesis | |
Associative hypothesis | |
Causal hypothesis | |
Null hypothesis | |
Alternative hypothesis | |
Working hypothesis | |
Statistical hypothesis | |
Logical hypothesis | |
Hypothesis-testing | |
Qualitative research questions | Qualitative research hypotheses |
Contextual research questions | Hypothesis-generating |
Descriptive research questions | |
Evaluation research questions | |
Explanatory research questions | |
Exploratory research questions | |
Generative research questions | |
Ideological research questions | |
Ethnographic research questions | |
Phenomenological research questions | |
Grounded theory questions | |
Qualitative case study questions |
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 .
Quantitative research questions | |
---|---|
Descriptive research question | |
- Measures responses of subjects to variables | |
- Presents variables to measure, analyze, or assess | |
What is the proportion of resident doctors in the hospital who have mastered ultrasonography (response of subjects to a variable) as a diagnostic technique in their clinical training? | |
Comparative research question | |
- Clarifies difference between one group with outcome variable and another group without outcome variable | |
Is there a difference in the reduction of lung metastasis in osteosarcoma patients who received the vitamin D adjunctive therapy (group with outcome variable) compared with osteosarcoma patients who did not receive the vitamin D adjunctive therapy (group without outcome variable)? | |
- Compares the effects of variables | |
How does the vitamin D analogue 22-Oxacalcitriol (variable 1) mimic the antiproliferative activity of 1,25-Dihydroxyvitamin D (variable 2) in osteosarcoma cells? | |
Relationship research question | |
- Defines trends, association, relationships, or interactions between dependent variable and independent variable | |
Is there a relationship between the number of medical student suicide (dependent variable) and the level of medical student stress (independent variable) in Japan during the first wave of the COVID-19 pandemic? |
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 .
Quantitative research hypotheses | |
---|---|
Simple hypothesis | |
- Predicts relationship between single dependent variable and single independent variable | |
If the dose of the new medication (single independent variable) is high, blood pressure (single dependent variable) is lowered. | |
Complex hypothesis | |
- Foretells relationship between two or more independent and dependent variables | |
The higher the use of anticancer drugs, radiation therapy, and adjunctive agents (3 independent variables), the higher would be the survival rate (1 dependent variable). | |
Directional hypothesis | |
- Identifies study direction based on theory towards particular outcome to clarify relationship between variables | |
Privately funded research projects will have a larger international scope (study direction) than publicly funded research projects. | |
Non-directional hypothesis | |
- Nature of relationship between two variables or exact study direction is not identified | |
- Does not involve a theory | |
Women and men are different in terms of helpfulness. (Exact study direction is not identified) | |
Associative hypothesis | |
- Describes variable interdependency | |
- Change in one variable causes change in another variable | |
A larger number of people vaccinated against COVID-19 in the region (change in independent variable) will reduce the region’s incidence of COVID-19 infection (change in dependent variable). | |
Causal hypothesis | |
- An effect on dependent variable is predicted from manipulation of independent variable | |
A change into a high-fiber diet (independent variable) will reduce the blood sugar level (dependent variable) of the patient. | |
Null hypothesis | |
- A negative statement indicating no relationship or difference between 2 variables | |
There is no significant difference in the severity of pulmonary metastases between the new drug (variable 1) and the current drug (variable 2). | |
Alternative hypothesis | |
- Following a null hypothesis, an alternative hypothesis predicts a relationship between 2 study variables | |
The new drug (variable 1) is better on average in reducing the level of pain from pulmonary metastasis than the current drug (variable 2). | |
Working hypothesis | |
- A hypothesis that is initially accepted for further research to produce a feasible theory | |
Dairy cows fed with concentrates of different formulations will produce different amounts of milk. | |
Statistical hypothesis | |
- Assumption about the value of population parameter or relationship among several population characteristics | |
- Validity tested by a statistical experiment or analysis | |
The mean recovery rate from COVID-19 infection (value of population parameter) is not significantly different between population 1 and population 2. | |
There is a positive correlation between the level of stress at the workplace and the number of suicides (population characteristics) among working people in Japan. | |
Logical hypothesis | |
- Offers or proposes an explanation with limited or no extensive evidence | |
If healthcare workers provide more educational programs about contraception methods, the number of adolescent pregnancies will be less. | |
Hypothesis-testing (Quantitative hypothesis-testing research) | |
- Quantitative research uses deductive reasoning. | |
- This involves the formation of a hypothesis, collection of data in the investigation of the problem, analysis and use of the data from the investigation, and drawing of conclusions to validate or nullify the hypotheses. |
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 research questions | |
---|---|
Contextual research question | |
- Ask the nature of what already exists | |
- Individuals or groups function to further clarify and understand the natural context of real-world problems | |
What are the experiences of nurses working night shifts in healthcare during the COVID-19 pandemic? (natural context of real-world problems) | |
Descriptive research question | |
- Aims to describe a phenomenon | |
What are the different forms of disrespect and abuse (phenomenon) experienced by Tanzanian women when giving birth in healthcare facilities? | |
Evaluation research question | |
- Examines the effectiveness of existing practice or accepted frameworks | |
How effective are decision aids (effectiveness of existing practice) in helping decide whether to give birth at home or in a healthcare facility? | |
Explanatory research question | |
- Clarifies a previously studied phenomenon and explains why it occurs | |
Why is there an increase in teenage pregnancy (phenomenon) in Tanzania? | |
Exploratory research question | |
- Explores areas that have not been fully investigated to have a deeper understanding of the research problem | |
What factors affect the mental health of medical students (areas that have not yet been fully investigated) during the COVID-19 pandemic? | |
Generative research question | |
- Develops an in-depth understanding of people’s behavior by asking ‘how would’ or ‘what if’ to identify problems and find solutions | |
How would the extensive research experience of the behavior of new staff impact the success of the novel drug initiative? | |
Ideological research question | |
- Aims to advance specific ideas or ideologies of a position | |
Are Japanese nurses who volunteer in remote African hospitals able to promote humanized care of patients (specific ideas or ideologies) in the areas of safe patient environment, respect of patient privacy, and provision of accurate information related to health and care? | |
Ethnographic research question | |
- Clarifies peoples’ nature, activities, their interactions, and the outcomes of their actions in specific settings | |
What are the demographic characteristics, rehabilitative treatments, community interactions, and disease outcomes (nature, activities, their interactions, and the outcomes) of people in China who are suffering from pneumoconiosis? | |
Phenomenological research question | |
- Knows more about the phenomena that have impacted an individual | |
What are the lived experiences of parents who have been living with and caring for children with a diagnosis of autism? (phenomena that have impacted an individual) | |
Grounded theory question | |
- Focuses on social processes asking about what happens and how people interact, or uncovering social relationships and behaviors of groups | |
What are the problems that pregnant adolescents face in terms of social and cultural norms (social processes), and how can these be addressed? | |
Qualitative case study question | |
- Assesses a phenomenon using different sources of data to answer “why” and “how” questions | |
- Considers how the phenomenon is influenced by its contextual situation. | |
How does quitting work and assuming the role of a full-time mother (phenomenon assessed) change the lives of women in Japan? |
Qualitative research hypotheses | |
---|---|
Hypothesis-generating (Qualitative hypothesis-generating research) | |
- Qualitative research uses inductive reasoning. | |
- This involves data collection from study participants or the literature regarding a phenomenon of interest, using the collected data to develop a formal hypothesis, and using the formal hypothesis as a framework for testing the hypothesis. | |
- Qualitative exploratory studies explore areas deeper, clarifying subjective experience and allowing formulation of a formal hypothesis potentially testable in a future quantitative approach. |
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 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
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.
Variables | Unclear and weak statement (Statement 1) | Clear and good statement (Statement 2) | Points to avoid |
---|---|---|---|
Research question | Which is more effective between smoke moxibustion and smokeless moxibustion? | “Moreover, regarding smoke moxibustion versus smokeless moxibustion, it remains unclear which is more effective, safe, and acceptable to pregnant women, and whether there is any difference in the amount of heat generated.” | 1) Vague and unfocused questions |
2) Closed questions simply answerable by yes or no | |||
3) Questions requiring a simple choice | |||
Hypothesis | The smoke moxibustion group will have higher cephalic presentation. | “Hypothesis 1. The smoke moxibustion stick group (SM group) and smokeless moxibustion stick group (-SLM group) will have higher rates of cephalic presentation after treatment than the control group. | 1) Unverifiable hypotheses |
Hypothesis 2. The SM group and SLM group will have higher rates of cephalic presentation at birth than the control group. | 2) Incompletely stated groups of comparison | ||
Hypothesis 3. There will be no significant differences in the well-being of the mother and child among the three groups in terms of the following outcomes: premature birth, premature rupture of membranes (PROM) at < 37 weeks, Apgar score < 7 at 5 min, umbilical cord blood pH < 7.1, admission to neonatal intensive care unit (NICU), and intrauterine fetal death.” | 3) Insufficiently described variables or outcomes | ||
Research objective | To determine which is more effective between smoke moxibustion and smokeless moxibustion. | “The specific aims of this pilot study were (a) to compare the effects of smoke moxibustion and smokeless moxibustion treatments with the control group as a possible supplement to ECV for converting breech presentation to cephalic presentation and increasing adherence to the newly obtained cephalic position, and (b) to assess the effects of these treatments on the well-being of the mother and child.” | 1) Poor understanding of the research question and hypotheses |
2) Insufficient description of population, variables, or study outcomes |
a These statements were composed for comparison and illustrative purposes only.
b These statements are direct quotes from Higashihara and Horiuchi. 16
Variables | Unclear and weak statement (Statement 1) | Clear and good statement (Statement 2) | Points to avoid |
---|---|---|---|
Research question | Does disrespect and abuse (D&A) occur in childbirth in Tanzania? | How does disrespect and abuse (D&A) occur and what are the types of physical and psychological abuses observed in midwives’ actual care during facility-based childbirth in urban Tanzania? | 1) Ambiguous or oversimplistic questions |
2) Questions unverifiable by data collection and analysis | |||
Hypothesis | Disrespect and abuse (D&A) occur in childbirth in Tanzania. | Hypothesis 1: Several types of physical and psychological abuse by midwives in actual care occur during facility-based childbirth in urban Tanzania. | 1) Statements simply expressing facts |
Hypothesis 2: Weak nursing and midwifery management contribute to the D&A of women during facility-based childbirth in urban Tanzania. | 2) Insufficiently described concepts or variables | ||
Research objective | To describe disrespect and abuse (D&A) in childbirth in Tanzania. | “This study aimed to describe from actual observations the respectful and disrespectful care received by women from midwives during their labor period in two hospitals in urban Tanzania.” | 1) Statements unrelated to the research question and hypotheses |
2) Unattainable or unexplorable objectives |
a This statement is a direct quote from Shimoda et al. 17
The other statements were composed for comparison and illustrative purposes only.
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.
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.
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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.
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:
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 , 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 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 .
Review our examples before placing an order, learn how to draft academic papers, 280+ quantitative research titles and 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.
Find Out the Difference Between Qualitative and Quantitative Research Methods
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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
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
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
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
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
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
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
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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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
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
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
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
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
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
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
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
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
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
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
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
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
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
Topic 276. Analysing the Impact of 3D Printing Technology on Manufacturing Costs: A Quantitative Study
Topic 277. Evaluating the Efficiency of Solar Panels in Different Climates: A Systematic Review
Topic 278. Assessing the Role of Big Data in Enhancing Healthcare Outcomes: A Case Study
Topic 279. Exploring the Effects of Electric Vehicles on Urban Air Quality: Challenges and Opportunities
Topic 280. Examining the Correlation Between STEM Education and Innovation in Technology: A Quantitative Study
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Methodology
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.
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.
A rule of thumb for deciding whether to use qualitative or quantitative data is:
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.
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”.
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.
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.
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:
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:
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.
Research 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 .
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:
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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Learn how to write up the quantitative results/findings/analysis chapter for your dissertation or thesis. Step-by-step guide + examples.
Recommended Citation Johnson, Daniel R., "A Quantitative Study of Teacher Perceptions of Professional Learning Communities' Context, Process, and Content" (2011). Seton Hall University Dissertations and Theses (ETDs). 15.
Sebring et al. (2003) found, "Our own and others' research convinced us that to achieve and sustain significant advances in instruction, leadership practice had to develop towards a model of distributed leadership" (p. 2). The authors referenced research conducted by the Consortium on Chicago School Research:
THE DIGNITY FOR ALL STUDENTS ACT: A QUANTITATIVE STUDY OF ONE UPSTATE NEW YORK PUBLIC SCHOOL IMPLEMENTATION By Christopher M. Riddell A doctoral dissertation Presented to the Graduate Faculty of the Doctor of Law and Policy Program at Northeastern University In partial fulfillment of the requirements for the degree of Doctor of Law and Policy
Learn how to write a clear and concise results section for your dissertation, with tips and examples to help you present your findings effectively.
The purpose of this study was to quantitatively examine the impact of social media. uted primarily by the millennial genera. ion on reaction of the audience to thecommodities or s. managers working for smartphone companies can leverage the services of highl.
Quantitative Research Dissertation Chapters 4 and 5 (Suggested Content) Information below is suggested content; seek guidance from committee chair about content of all chapters in the dissertation.
An overview of how to structure quantitative research questions for a dissertation or thesis.
Dissertation examples. 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.
The book does present my recommendations for designing and executing quantitative and qualitative dissertation research based on my own experience writing a dissertation, reading other dissertations, and directing dissertations.
Explore the types of quantitative research methods and determine which is ideal for your dissertation. Apply to the College of Doctoral Studies at GCU.
The purpose of this study was to conduct a quantitative, quasi-experimental assessment. of an online high school mathematics remediation program to determine if the remediation. program was successful in its endeavor to remediate students. This research study, informed by.
Guidance for every stage of your research project, from planning to writing up.
Quantitative research is the process of collecting and analyzing numerical data. It can be used to find patterns and averages, make predictions, test causal relationships, and generalize results to wider populations.
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.
Quantitative Dissertations The Quantitative Dissertations part of Lærd Dissertation helps guide you through the process of doing a quantitative dissertation. 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 ...
Download our free template for the dissertation/thesis results chapter. Covers qual and quant studies, including instructions and examples.
Learn how to turn a weak research question into a strong one with examples suitable for a research paper, thesis or dissertation.
Prepared by. NOTE: This proposal is included in the ancillary materials of Research Design with permission of the author. Hayes, M. M. (2007). Design and analysis of the student strengths index (SSI) for nontraditional graduate students. Unpublished master's thesis. University of Nebraska, Lincoln, NE.
A strong theoretical framework gives your research direction. It allows you to convincingly interpret, explain, and generalize from your findings and show the relevance of your thesis or dissertation topic in your field.
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 ...
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.
When collecting and analyzing data, quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.