The document provides a comprehensive overview of quantitative and qualitative research methods, detailing their definitions, key characteristics, advantages, and methodologies. It highlights the structured approach of quantitative research which emphasizes numeric data, objectivity, and statistical analysis, alongside the subjectivity and depth associated with qualitative research. Additionally, best practices for both methods and a comparison between them are discussed, offering insights into when to utilize each approach.

1. Quantitative & Qualitative
Research Methods
Ayat Comp Department of Education
Khawaja Fareed University of Engineering & Information
Technology (RYK)

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Content List
Topic: Concept of Qualitative & Quantitative Research Design
1. Quantitative Research
Definition
What is Quantitative Research?
Characteristics of Quantitative Research
Quantitative Key Characteristics
1. Objectivity
2. Structures approach
3. Numeric Data
4. Large Sample size
5. Standardized data collection
6. Deductive reasoning
7. Replication
8. Statistical Analysis
9. Precision
10. Generalizability
Main Characteristics
Quantitative Research Key advantages
1. Precision
2. Test Hypothesis
3. Quantify Relationships
4. Efficiency
5. Easy to Compare
Quantitative Research Methodology
1. Primary Method
1. Surveys
2. Experiment
3. Observational study
4. Content Analysis
5. Psychometrics
2. Secondary Method

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Things to keep in mind when reporting the results of a study using Quantitative methods
7 Best practices to Conduct Quantitative Research
1. Clearly define the research question
2. Use a well-designed research design
3. Use validated and reliable instruments
4. Ensure informed consent
5. Minimize bias
6. Ensure data security and confidentiality
7. Use appropriate statistical analysis
Basic Research Design for Quantitative Research Study
1. Introduction
2. Identifies the research problem
3. Review the literature
4. Describe the theoretical framework
5. Methodology
6. Study population and sampling
7. Data collection
8. Data analysis
9. Results
10. Statistical analysis
11. Discussion
12. Interpretation of results
13. Discussion and implementations
14. Limitations
15. Conclusions
16. Summary of findings
17. Recommendations
18. Future research
Strengths of using Quantitative methods
Limitations of using Quantitative Method
2. Qualitative Research
Definition
What is Qualitative Research?
Key Characteristics of Qualitative Research

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1. Subjectivity
2. Contextualization
3. Flexibility
4. Richness and depth
5. Inductive reasoning
6. Naturalistic reasoning
Three key elements of Qualitative research
1. The Design
1. Naturalistic
2. Emergent
3. Purposeful
2. The collection of data
1. Data
2. Personal experience and engagement
3. Empathic neutrality
4. Dynamic systems
3. The Analysis
1. Unique case orientation
2. Inductive analysis
3. Holistic perspective
4. Context sensitive
5. Voice, perspective, and reflexivity
Basic research design for Qualitative Studies
1. Goals
2. Conceptual framework
3. Research questions
4. Method
5. Validity
6. Conclusion
Strengths of using Qualitative method
Limitations of using Qualitative method
5 key types of Qualitative Research
1. Phenomenology
2. Ethnography
3. Grounded Theory
4. Case Study

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5. Narrative Research
Qualitative Research Methods: The Top 4 Techniques
1. In-Depth Interviews
2. Focus groups
3. Observational research
4. Case studies
Qualitative Research Best Practices
1. Sampling Strategy
2. Data Collection Rigor
3. Ethical Considerations
4. Data analysis
5. Triangulation
6. Member checking
7. Reflexive Journaling
8. Clear and Transparent Reporting
Topic: Comparison of Qualitative & Quantitative Research
Quantitative Research
1. What is Quantitative Research?
2. When to use Quantitative Research
3. Benefits of Quantitative Research
4. Quantitative Research Example
Qualitative Research
1. What is Qualitative Research?
2. When to use Qualitative Research
3. Benefits of Quantitative Research
4. Quantitative Research Example
Qualitative Vs. Quantitative Research – A Comparison
Qualitative & Quantitative Research Data Collection Methods
Data Collection methods
Quantitative Data Collection Methods
1. Surveys

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2. Observations
3. Experiments
Qualitative Data Collection Methods
1. Interviews
2. Focus groups
3. Ethnography
4. Literature Review
When to use qualitative vs. quantitative research
A Step-wise Guide to Conduct Qualitative and Quantitative Research
Research Questions
1. Quantitative research approach
2. Qualitative research approach
3. Mixed methods approach
How to analyze qualitative and quantitative data
1. Analyzing quantitative data
2. Analyzing qualitative data
3. Qualitative content analysis
4. Discourse Analysis
Conclusion

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Topic: Concept of Qualitative & Quantitative
Research Design
Quantitative Research
Definition
Quantitative methods emphasize objective measurements and the statistical, mathematical, or
numerical analysis of data collected through polls, questionnaires, and surveys, or by
manipulating pre-existing statistical data using computational techniques. Quantitative research
focuses on gathering numerical data and generalizing it across groups of people or to explain a
particular phenomenon.
What is Quantitative Research?
Quantitative research stands as a powerful research methodology dedicated to the systematic
collection and analysis of measurable data. Through rigorous statistical and mathematical
techniques, this method extracts insights from structured surveys, controlled experiments, or
other defined data-gathering methods.
The primary objective of quantitative research is to measure and quantify variables,
relationships, and patterns within the dataset. By testing hypotheses, making predictions, and
drawing generalizable conclusions, it plays a crucial role in fields such as psychology, sociology,
economics, and education. This approach often involves significant sample sizes, ensuring robust
results.
Explore the depth of quantitative research with this comprehensive guide, offering practical
examples and applications to demonstrate its real-world impact. Stay updated with the latest
trends and developments in quantitative research as we continually refine our insights to provide
you with the most relevant and cutting-edge information.
Characteristics of Quantitative Research
Your goal in conducting quantitative research study is to determine the relationship between one
thing [an independent variable] and another [a dependent or outcome variable] within a
population. Quantitative research designs are either descriptive [subjects usually measured

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once] or experimental [subjects measured before and after a treatment]. A descriptive study
establishes only associations between variables; an experimental study establishes causality.
Quantitative research deals in numbers, logic, and an objective stance. Quantitative research
focuses on numeric and unchanging data and detailed, convergent reasoning rather than
divergent reasoning [i.e., the generation of a variety of ideas about a research problem in a
spontaneous, free-flowing manner].
Quantitative Research: Key Characteristics
Below are the key characteristics of quantitative research:
1. Objectivity:
Quantitative research is grounded in the principles of objectivity and empiricism, which means
that the research is focused on observable and measurable phenomena, rather than personal
opinions or experiences.
2. Structured approach:

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Quantitative research follows a structured and systematic approach to data collection and
analysis, using clearly defined variables, hypotheses, and research questions.
3. Numeric data:
Quantitative research uses numerical data to describe and analyze the phenomena under study,
such as statistical analysis, surveys, and experiments.
4. Large sample size:
Quantitative research often involves large sample sizes to ensure statistical significance and to
generalize findings to a larger population.
5. Standardized data collection:
Quantitative research typically involves standardized data collection methods, such as surveys or
experiments, to minimize potential sources of bias and increase reliability.
6. Deductive reasoning:
Quantitative research uses deductive reasoning, where the researcher tests a specific hypothesis
based on prior knowledge and theory.
7. Replication:
Quantitative research emphasizes the importance of replication, where other researchers can
reproduce the study’s methods and obtain similar results.
8. Statistical analysis:
Quantitative research involves statistical analysis to analyze the data and test the research
hypotheses, often using software programs to assist with data analysis.
9. Precision:
Quantitative research aims to be precise in its measurement and analysis of data. It seeks to
quantify and measure the specific aspects of a phenomenon being studied.
10. Generalizability:

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Quantitative research aims to generalize findings from a sample to a larger population. It seeks
to draw conclusions that apply to a broader group beyond the specific sample being studied.
Main characteristics
The data is usually gathered using structured research instruments.
The results are based on larger sample sizes that are representative of the population.
The research study can usually be replicated or repeated, given its high reliability.
Researcher has a clearly defined research question to which objective answers are sought.
All aspects of the study are carefully designed before data is collected.
Data are in the form of numbers and statistics, often arranged in tables, charts, figures,
or other non-textual forms.
Project can be used to generalize concepts more widely, predict future results, or
investigate causal relationships.
Researcher uses tools, such as questionnaires or computer software, to collect numerical
data.
The overarching aim of a quantitative research study is to classify features, count them, and
construct statistical models in an attempt to explain what is observed.
Quantitative Research: Key Advantages

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The advantages of quantitative research make it a valuable research method in a variety of fields,
particularly in fields that require precise measurement and testing of hypotheses.
Precision:
Quantitative research aims to be precise in its measurement and analysis of data. This can
increase the accuracy of the results and enable researchers to make more precise predictions.
Test hypotheses:
Quantitative research is well-suited for testing specific hypotheses or research questions,
allowing researchers to draw clear conclusions and make predictions based on the data.
Quantify relationships:
Quantitative research enables researchers to quantify and measure relationships between
variables, allowing for more precise and quantitative comparisons.
Efficiency:

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Quantitative research often involves the use of standardized procedures and data collection
methods, which can make the research process more efficient and reduce the amount of time
and resources required.
Easy to compare:
Quantitative research often involves the use of standardized measures and scales, which makes
it easier to compare results across different studies or populations.
Ability to detect small effects: Quantitative research is often able to detect small effects that may
not be observable through qualitative research methods, due to the use of statistical analysis and
large sample sizes.
Quantitative Research Methodology
Quantitative research is a type of research that focuses on collecting and analyzing numerical
data to answer research questions. There are two main methods used to conduct quantitative
research:
1. Primary Method
There are several methods of primary quantitative research, each with its own strengths and
limitations.
Surveys:
Surveys are a common method of quantitative research and involve collecting data from a sample
of individuals using standardized questionnaires or interviews. Surveys can be conducted in
various ways, such as online, by mail, by phone, or in person. Surveys can be used to study
attitudes, behaviors, opinions, and demographics.
One of the main advantages of surveys is that they can be conducted on a large scale, making it
possible to obtain representative data from a population. However, surveys can suffer from
issues such as response bias, where participants may not provide accurate or truthful answers,
and nonresponse bias, where certain groups may be less likely to participate in the survey.
Experiments:
Experiments involve manipulating one or more variables to determine their effects on an
outcome of interest. Experiments can be carried out in controlled laboratory settings or in real-

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world field environments. Experiments can be used to test causal relationships between variables
and to establish cause-and-effect relationships.
One of the main advantages of experiments is that they provide a high level of control over the
variables being studied, which can increase the internal validity of the study. However,
experiments can suffer from issues such as artificiality, where the experimental setting may not
accurately reflect real-world situations, and demand characteristics, where participants may
change their behavior due to the experimental setting.
Observational studies:
Observational studies involve observing and recording data without manipulating any variables.
Observational studies can be conducted in various settings, such as naturalistic environments or
controlled laboratory settings. Observational studies can be used to study behaviors,
interactions, and phenomena that cannot be manipulated experimentally.
One of the main advantages of observational studies is that they can provide rich and detailed
data about real-world phenomena. However, observational studies can suffer from issues such
as observer bias, where the observer may interpret the data in a subjective manner, and
reactivity, where the presence of the observer may change the behavior being observed.
Content analysis:
Content analysis involves analyzing media or communication content, such as text, images, or
videos, to identify patterns or trends. Content analysis can be used to study media
representations of social issues or to identify patterns in social media data.
One of the main advantages of content analysis is that it can provide insights into the cultural
and social values reflected in media content. However, content analysis can suffer from issues
such as the subjectivity of the coding process and the potential for errors or bias in the data
collection process.
Psychometrics:
Psychometrics involves the development and validation of standardized tests or measures, such
as personality tests or intelligence tests. Psychometrics can be used to study individual

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differences in psychological traits and to assess the validity and reliability of psychological
measures.
One of the main advantages of psychometrics is that it can provide a standardized and objective
way to measure psychological constructs. However, psychometrics can suffer from issues such
as the cultural specificity of the measures and the potential for response bias in self-report
measures.
2. Secondary Method
Secondary quantitative research methods involve analyzing existing data that was collected for
other purposes. This can include data from government records, public opinion polls, or market
research studies. Secondary research is often quicker and less expensive than primary research,
but it may not provide data that is as specific to the research question.
One of the main advantages of secondary data analysis is that it can be a cost-effective way to
obtain large amounts of data. However, secondary data analysis can suffer from issues such as
the quality and relevance of the data, and the potential for missing or incomplete data.
Things to keep in mind when reporting the results of a study using
Quantitative methods
Explain the data collected and their statistical treatment as well as all relevant results
in relation to the research problem you are investigating. Interpretation of results is
not appropriate in this section.
Report unanticipated events that occurred during your data collection. Explain how
the actual analysis differs from the planned analysis. Explain your handling of missing
data and why any missing data does not undermine the validity of your analysis.
Explain the techniques you used to "clean" your data set.
Choose a minimally sufficient statistical procedure; provide a rationale for its use and
a reference for it. Specify any computer programs used.
Describe the assumptions for each procedure and the steps you took to ensure that
they were not violated.
When using inferential statistics, provide the descriptive statistics, confidence
intervals, and sample sizes for each variable as well as the value of the test statistic,
its direction, the degrees of freedom, and the significance level [report the actual p
value].
Avoid inferring causality, particularly in nonrandomized designs or without further
experimentation.

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Use tables to provide exact values; use figures to convey global effects. Keep figures
small in size; include graphic representations of confidence intervals whenever
possible.
Always tell the reader what to look for in tables and figures.
7 Best Practices to Conduct Quantitative Research
Here are the key best practices that should be followed when conducting quantitative research:
1. Clearly define the research question:
The research question should be specific, measurable, and focused on a clear problem or issue.
2. Use a well-designed research design:
The research design should be appropriate for the research question, and should include a clear
sampling strategy, data collection methods, and statistical analysis plan.
3. Use validated and reliable instruments:
The instruments used to collect data should be validated and reliable to ensure that the data
collected is accurate and consistent.
4. Ensure informed consent:

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Participants should be fully informed about the purpose of the research, their rights, and how
their data will be used. Informed consent should be obtained before data collection begins.
5. Minimize bias:
Researchers should take steps to minimize bias in all stages of the research process, including
study design, data collection, and data analysis.
6. Ensure data security and confidentiality:
Data should be kept secure and confidential to protect the privacy of participants and prevent
unauthorized access.
7. Use appropriate statistical analysis:
Statistical analysis should be appropriate for the research question and the data collected.
Accurate and clear reporting of results is imperative in quantitative research.
Basic Research Design for Quantitative Studies
Before designing a quantitative research study, you must decide whether it will be descriptive or
experimental because this will dictate how you gather, analyze, and interpret the results. A
descriptive study is governed by the following rules: subjects are generally measured once; the
intention is to only establish associations between variables; and, the study may include a sample
population of hundreds or thousands of subjects to ensure that a valid estimate of a generalized
relationship between variables has been obtained. An experimental design includes subjects
measured before and after a particular treatment, the sample population may be very small and
purposefully chosen, and it is intended to establish causality between variables.
1. Introduction
The introduction to a quantitative study is usually written in the present tense and from the third
person point of view. It covers the following information:
2. Identifies the research problem
As with any academic study, you must state clearly and concisely the research problem being
investigated.
3. Reviews the literature

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Review scholarship on the topic, synthesizing key themes and, if necessary, noting studies that
have used similar methods of inquiry and analysis. Note where key gaps exist and how your study
helps to fill these gaps or clarifies existing knowledge.
4. Describes the theoretical framework
Provide an outline of the theory or hypothesis underpinning your study. If necessary, define
unfamiliar or complex terms, concepts, or ideas and provide the appropriate background
information to place the research problem in proper context [e.g., historical, cultural, economic,
etc.].
5. Methodology
The methods section of a quantitative study should describe how each objective of your study
will be achieved. Be sure to provide enough detail to enable the reader can make an informed
assessment of the methods being used to obtain results associated with the research problem.
The methods section should be presented in the past tense.
6. Study population and sampling
Where did the data come from; how robust is it; note where gaps exist or what was excluded.
Note the procedures used for their selection;
7. Data collection
describe the tools and methods used to collect information and identify the variables being
measured; describe the methods used to obtain the data; and, note if the data was pre-existing
[i.e., government data] or you gathered it yourself. If you gathered it yourself, describe what type
of instrument you used and why. Note that no data set is perfect--describe any limitations in
methods of gathering data.
8. Data analysis
Describe the procedures for processing and analyzing the data. If appropriate, describe the
specific instruments of analysis used to study each research objective, including mathematical
techniques and the type of computer software used to manipulate the data.
9. Results
The finding of your study should be written objectively and in a succinct and precise format. In
quantitative studies, it is common to use graphs, tables, charts, and other non-textual elements

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to help the reader understand the data. Make sure that non-textual elements do not stand in
isolation from the text but are being used to supplement the overall description of the results
and to help clarify key points being made. Further information about how to effectively present
data using charts and graphs can be found here.
10. Statistical analysis
How did you analyze the data? What were the key findings from the data? The findings should
be present in a logical, sequential order. Describe but do not interpret these trends or negative
results; save that for the discussion section. The results should be presented in the past tense.
11. Discussion
Discussions should be analytic, logical, and comprehensive. The discussion should meld together
your findings in relation to those identified in the literature review, and placed within the context
of the theoretical framework underpinning the study. The discussion should be presented in the
present tense.
12. Interpretation of results
Reiterate the research problem being investigated and compare and contrast the findings with
the research questions underlying the study. Did they affirm predicted outcomes or did the data
refute it?
Description of trends, comparison of groups, or relationships among variables -- describe any
trends that emerged from your analysis and explain all unanticipated and statistical insignificant
findings.
13. Discussion of implications
What is the meaning of your results? Highlight key findings based on the overall results and note
findings that you believe are important. How have the results helped fill gaps in understanding
the research problem?
14. Limitations
Describe any limitations or unavoidable bias in your study and, if necessary, note why these
limitations did not inhibit effective interpretation of the results.
15. Conclusion

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End your study by to summarizing the topic and provide a final comment and assessment of the
study.
16. Summary of findings
Synthesize the answers to your research questions. Do not report any statistical data here; just
provide a narrative summary of the key findings and describe what was learned that you did not
know before conducting the study.
17. Recommendations
If appropriate to the aim of the assignment, tie key findings with policy recommendations or
actions to be taken in practice.
18. Future research
Note the need for future research linked to your study’s limitations or to any remaining gaps in
the literature that were not addressed in your study.
Strengths of Using Quantitative Methods
Quantitative researchers try to recognize and isolate specific variables contained within the study
framework, seek correlation, relationships and causality, and attempt to control the environment
in which the data is collected to avoid the risk of variables, other than the one being studied,
accounting for the relationships identified.
Among the specific strengths of using quantitative methods to study social science research
problems:
Allows for a broader study, involving a greater number of subjects, and enhancing the
generalization of the results;
Allows for greater objectivity and accuracy of results. Generally, quantitative methods
are designed to provide summaries of data that support generalizations about the
phenomenon under study. In order to accomplish this, quantitative research usually
involves few variables and many cases, and employs prescribed procedures to ensure
validity and reliability;
Applying well established standards means that the research can be replicated, and
then analyzed and compared with similar studies;
You can summarize vast sources of information and make comparisons across
categories and over time; and,

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Personal bias can be avoided by keeping a 'distance' from participating subjects and
using accepted computational techniques.
Limitations of Using Quantitative Methods
Quantitative methods presume to have an objective approach to studying research problems,
where data is controlled and measured, to address the accumulation of facts, and to determine
the causes of behavior. As a consequence, the results of quantitative research may be statistically
significant but are often humanly insignificant.
Some specific limitations associated with using quantitative methods to study research problems
in the social sciences include:
Quantitative data is more efficient and able to test hypotheses, but may miss contextual
detail;
Uses a static and rigid approach and so employs an inflexible process of discovery;
The development of standard questions by researchers can lead to "structural bias" and
false representation, where the data actually reflects the view of the researcher instead
of the participating subject;
Results provide less detail on behavior, attitudes, and motivation;
Researcher may collect a much narrower and sometimes superficial dataset;
Results are limited as they provide numerical descriptions rather than detailed narrative
and generally provide less elaborate accounts of human perception;
The research is often carried out in an unnatural, artificial environment so that a level of
control can be applied to the exercise. This level of control might not normally be in place
in the real world thus yielding "laboratory results" as opposed to "real world results"; and,
Preset answers will not necessarily reflect how people really feel about a subject and, in
some cases, might just be the closest match to the preconceived hypothesis.
Qualitative Research
Definition
The word qualitative implies an emphasis on the qualities of entities and on processes and
meanings that are not experimentally examined or measured [if measured at all] in terms of
quantity, amount, intensity, or frequency. Qualitative researchers stress the socially constructed
nature of reality, the intimate relationship between the researcher and what is studied, and the
situational constraints that shape inquiry. Such researchers emphasize the value-laden nature of
inquiry. They seek answers to questions that stress how social experience is created and given
meaning. In contrast, quantitative studies emphasize the measurement and analysis of causal

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relationships between variables, not processes. Qualitative forms of inquiry are considered by
many social and behavioral scientists to be as much a perspective on how to approach
investigating a research problem as it is a method.
What is Qualitative Research?
Qualitative research is defined as an exploratory method that aims to understand complex
phenomena, often within their natural settings, by examining subjective experiences, beliefs,
attitudes, and behaviors.
Unlike quantitative research, which focuses on numerical measurements and statistical analysis,
qualitative research employs a range of data collection methods to gather detailed, non-
numerical data that can provide in-depth insights into the research topic.
Key Characteristics of Qualitative Research
1. Subjectivity:
Qualitative research acknowledges the subjective nature of human experiences and perceptions.
It recognizes that individuals interpret and construct meaning based on their unique
perspectives, cultural backgrounds, and social contexts. Researchers using qualitative methods
aim to capture this subjectivity by engaging in detailed qualitative observations, interviews, and
analyses that capture the nuances and complexities of human behavior.
2. Contextualization:
Qualitative research places a strong emphasis on the context in which social phenomena occur.
It seeks to understand the interconnectedness between individuals, their environments, and the

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broader social structures that shape their experiences. Researchers delve into the specific
settings and circumstances that influence the behavior and attitudes of participants, aiming to
unravel the intricate relationships between different variables.
3. Flexibility:
Qualitative research is characterized by its flexibility and adaptability. Researchers have the
freedom to modify their research design and methods during the course of the study based on
emerging insights and new directions. This flexibility allows for iterative and exploratory
research, enabling researchers to delve deeper into the subject matter and capture unexpected
findings.
Interpretation and meaning-making: Qualitative research recognizes that meaning is not fixed
but constructed through social interactions and interpretations. Researchers engage in a process
of interpretation and meaning-making to make sense of the data collected. This interpretive
approach allows researchers to explore multiple perspectives, cultural influences, and social
constructions that shape participants’ experiences and behaviors.
4. Richness and depth:
One of the key strengths of qualitative research is its ability to generate rich and in-depth data.
Through methods such as interviews, focus groups, and participant observation, researchers can
gather detailed narratives and descriptions that go beyond surface-level information. This depth
of data enables a comprehensive understanding of the research topic, including the underlying
motivations, emotions, and social dynamics at play.
5. Inductive reasoning:
Qualitative research often employs an inductive reasoning approach. Instead of starting with
preconceived hypotheses or theories, researchers allow patterns and themes to emerge from
the data. They engage in iterative cycles of data collection and analysis to develop theories or
conceptual frameworks grounded in the empirical evidence gathered. This inductive process
allows for new insights and discoveries that may challenge existing theories or offer alternative
explanations.
6. Naturalistic setting:

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Qualitative research frequently takes place in naturalistic settings, where participants are
observed and studied in their everyday environments. This setting enhances the ecological
validity of the research, as it allows researchers to capture authentic behaviors, interactions, and
experiences. By observing individuals in their natural contexts, researchers can gain a deeper
understanding of how social phenomena unfold in real-world situations.
Three Key Elements of Qualitative Research
Below are the three key elements that define a qualitative research study and the applied forms
each take in the investigation of a research problem.
1. The Design
1. Naturalistic
Refers to studying real-world situations as they unfold naturally; non-manipulative and non-
controlling; the researcher is open to whatever emerges [i.e., there is a lack of predetermined
constraints on findings].
2. Emergent
1. The Design
2. The
Collection
of Data
3. The
Analysis

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Acceptance of adapting inquiry as understanding deepens and/or situations change; the
researcher avoids rigid designs that eliminate responding to opportunities to pursue new paths
of discovery as they emerge.
3. Purposeful
Cases for study [e.g., people, organizations, communities, cultures, events, critical incidences]
are selected because they are “information rich” and illuminative. That is, they offer useful
manifestations of the phenomenon of interest; sampling is aimed at insight about the
phenomenon, not empirical generalization derived from a sample and applied to a population.
2. The Collection of Data
1. Data
Observations yield a detailed, "thick description" [in-depth understanding]; interviews capture
direct quotations about people’s personal perspectives and lived experiences; often derived from
carefully conducted case studies and review of material culture.
2. Personal experience and engagement
Researcher has direct contact with and gets close to the people, situation, and phenomenon
under investigation; the researcher’s personal experiences and insights are an important part of
the inquiry and critical to understanding the phenomenon.
3. Empathic neutrality
An empathic stance in working with study respondents seeks vicarious understanding without
judgment [neutrality] by showing openness, sensitivity, respect, awareness, and responsiveness;
in observation, it means being fully present [mindfulness].
4. Dynamic systems
There is attention to process; assumes change is ongoing, whether the focus is on an individual,
an organization, a community, or an entire culture, therefore, the researcher is mindful of and
attentive to system and situational dynamics.
3. The Analysis
1. Unique case orientation

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Assumes that each case is special and unique; the first level of analysis is being true to, respecting,
and capturing the details of the individual cases being studied; cross-case analysis follows from
and depends upon the quality of individual case studies.
2. Inductive analysis
Immersion in the details and specifics of the data to discover important patterns, themes, and
inter-relationships; begins by exploring, then confirming findings, guided by analytical principles
rather than rules.
3. Holistic perspective
The whole phenomenon under study is understood as a complex system that is more than the
sum of its parts; the focus is on complex interdependencies and system dynamics that cannot be
reduced in any meaningful way to linear, cause and effect relationships and/or a few discrete
variables.
4. Context sensitive
Places findings in a social, historical, and temporal context; researcher is careful about [even
dubious of] the possibility or meaningfulness of generalizations across time and space;
emphasizes careful comparative case study analysis and extrapolating patterns for possible
transferability and adaptation in new settings.
5. Voice, perspective, and reflexivity
The qualitative methodologist owns and is reflective about her or his own voice and perspective;
a credible voice conveys authenticity and trustworthiness; complete objectivity being impossible
and pure subjectivity undermining credibility, the researcher's focus reflects a balance between
understanding and depicting the world authentically in all its complexity and of being self-
analytical, politically aware, and reflexive in consciousness.
Basic Research Design for Qualitative Studies
Unlike positivist or experimental research that utilizes a linear and one-directional sequence of
design steps, there is considerable variation in how a qualitative research study is organized. In
general, qualitative researchers attempt to describe and interpret human behavior based
primarily on the words of selected individuals [a.k.a., “informants” or “respondents”] and/or
through the interpretation of their material culture or occupied space. There is a reflexive process
underpinning every stage of a qualitative study to ensure that researcher biases, presuppositions,
and interpretations are clearly evident, thus ensuring that the reader is better able to interpret

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the overall validity of the research. According to Maxwell (2009), there are five, not necessarily
ordered or sequential, components in qualitative research designs. How they are presented
depends upon the research philosophy and theoretical framework of the study, the methods
chosen, and the general assumptions underpinning the study.
1. Goals
Describe the central research problem being addressed but avoid describing any anticipated
outcomes. Questions to ask yourself are: Why is your study worth doing? What issues do you
want to clarify, and what practices and policies do you want it to influence? Why do you want to
conduct this study, and why should the reader care about the results?
2. Conceptual Framework
Questions to ask yourself are: What do you think is going on with the issues, settings, or people
you plan to study? What theories, beliefs, and prior research findings will guide or inform your
research, and what literature, preliminary studies, and personal experiences will you draw upon
for understanding the people or issues you are studying? Note to not only report the results of
other studies in your review of the literature, but note the methods used as well. If appropriate,
describe why earlier studies using quantitative methods were inadequate in addressing the
research problem.
3. Research Questions
Usually there is a research problem that frames your qualitative study and that influences your
decision about what methods to use, but qualitative designs generally lack an accompanying
hypothesis or set of assumptions because the findings are emergent and unpredictable. In this
context, more specific research questions are generally the result of an interactive design process
rather than the starting point for that process. Questions to ask yourself are: What do you
specifically want to learn or understand by conducting this study? What do you not know about
the things you are studying that you want to learn? What questions will your research attempt
to answer, and how are these questions related to one another?
4. Methods
Structured approaches to applying a method or methods to your study help to ensure that there
is comparability of data across sources and researchers and, thus, they can be useful in answering
questions that deal with differences between phenomena and the explanation for these
differences [variance questions]. An unstructured approach allows the researcher to focus on the
particular phenomena studied. This facilitates an understanding of the processes that led to

27. 26
specific outcomes, trading generalizability and comparability for internal validity and contextual
and evaluative understanding. Questions to ask yourself are: What will you actually do in
conducting this study? What approaches and techniques will you use to collect and analyze your
data, and how do these constitute an integrated strategy?
5. Validity
In contrast to quantitative studies where the goal is to design, in advance, “controls” such as
formal comparisons, sampling strategies, or statistical manipulations to address anticipated and
unanticipated threats to validity, qualitative researchers must attempt to rule out most threats
to validity after the research has begun by relying on evidence collected during the research
process itself in order to effectively argue that any alternative explanations for a phenomenon
are implausible. Questions to ask yourself are: How might your results and conclusions be wrong?
What are the plausible alternative interpretations and validity threats to these, and how will you
deal with these? How can the data that you have, or that you could potentially collect, support
or challenge your ideas about what’s going on? Why should we believe your results?
6. Conclusion
Although Maxwell does not mention a conclusion as one of the components of a qualitative
research design, you should formally conclude your study. Briefly reiterate the goals of your study
and the ways in which your research addressed them. Discuss the benefits of your study and how
stakeholders can use your results. Also, note the limitations of your study and, if appropriate,
place them in the context of areas in need of further research.
Strengths of Using Qualitative Methods
The advantage of using qualitative methods is that they generate rich, detailed data that leave
the participants' perspectives intact and provide multiple contexts for understanding the
phenomenon under study. In this way, qualitative research can be used to vividly demonstrate
phenomena or to conduct cross-case comparisons and analysis of individuals or groups.
Among the specific strengths of using qualitative methods to study social science research
problems is the ability to:
Obtain a more realistic view of the lived world that cannot be understood or experienced
in numerical data and statistical analysis;
Provide the researcher with the perspective of the participants of the study through
immersion in a culture or situation and as a result of direct interaction with them;
Allow the researcher to describe existing phenomena and current situations;

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Develop flexible ways to perform data collection, subsequent analysis, and interpretation
of collected information;
Yield results that can be helpful in pioneering new ways of understanding;
Respond to changes that occur while conducting the study ]e.g., extended fieldwork or
observation] and offer the flexibility to shift the focus of the research as a result;
Provide a holistic view of the phenomena under investigation;
Respond to local situations, conditions, and needs of participants;
Interact with the research subjects in their own language and on their own terms; and,
Create a descriptive capability based on primary and unstructured data.
Limitations of Using Qualitative Methods
It is very much true that most of the limitations you find in using qualitative research techniques
also reflect their inherent strengths. For example, small sample sizes help you investigate
research problems in a comprehensive and in-depth manner. However, small sample sizes
undermine opportunities to draw useful generalizations from, or to make broad policy
recommendations based upon, the findings. Additionally, as the primary instrument of
investigation, qualitative researchers are often embedded in the cultures and experiences of
others. However, cultural embeddedness increases the opportunity for bias generated from
conscious or unconscious assumptions about the study setting to enter into how data is gathered,
interpreted, and reported.
Some specific limitations associated with using qualitative methods to study research problems
in the social sciences include the following:
Drifting away from the original objectives of the study in response to the changing nature
of the context under which the research is conducted;
Arriving at different conclusions based on the same information depending on the
personal characteristics of the researcher;
Replication of a study is very difficult;
Research using human subjects increases the chance of ethical dilemmas that undermine
the overall validity of the study;
An inability to investigate causality between different research phenomena;
Difficulty in explaining differences in the quality and quantity of information obtained
from different respondents and arriving at different, non-consistent conclusions;
Data gathering and analysis is often time consuming and/or expensive;
Requires a high level of experience from the researcher to obtain the targeted
information from the respondent;

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May lack consistency and reliability because the researcher can employ different probing
techniques and the respondent can choose to tell some particular stories and ignore
others; and,
Generation of a significant amount of data that cannot be randomized into manageable
parts for analysis.
5 Key Types of Qualitative Research
Here are the 5 key qualitative research types that are employed in studies:
1. Phenomenology:
This type of research focuses on understanding the essence and meaning of a particular
phenomenon or experience as perceived by individuals who have lived through it. It seeks to
capture the subjective experiences and perspectives of participants.
2. Ethnography:

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Ethnographic research involves immersing oneself in a specific cultural or social group to observe
and understand its practices, customs, beliefs, and values. Researchers spend extended periods
of time within the community to gain a holistic view of its way of life.
3. Grounded Theory:
Grounded theory aims to generate new theories or conceptual frameworks based on the analysis
of data collected from interviews, observations, or documents. It involves systematically coding
and categorizing data to identify patterns and develop theoretical explanations.
4. Case Study:
In a case study, researchers conduct an in-depth examination of a single individual, group, or
event to gain a detailed understanding of the subject of study. This approach allows for rich
contextual information and can be particularly useful in exploring complex and unique cases.
5. Narrative Research:
Narrative research focuses on analyzing the stories and personal narratives of individuals to gain
insights into their experiences, identities, and sense-making processes. It emphasizes the power
of storytelling in constructing meaning.
Qualitative Research Methods: The Top 4 Techniques

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Here are the best qualitative research methods that offer unique advantages in capturing rich
data, facilitating in-depth analysis, and generating comprehensive findings:
1. In-Depth Interviews
One of the most widely used qualitative research techniques is in-depth interviews. This method
involves conducting one-on-one interviews with participants to gather rich, detailed information
about their experiences, perspectives, and opinions. In-depth interviews allow researchers to
explore a participant’s thoughts, emotions, and motivations, providing deep insights into their
behavior and decision-making processes. The flexibility of this method allows for the exploration
of individual experiences in great detail, making it particularly suitable for sensitive topics or
complex phenomena. Through careful probing and open-ended questioning, researchers can
develop a comprehensive understanding of the participant’s worldview, uncovering hidden
patterns, and generating new hypotheses.
2. Focus Groups
Focus group research involves the gathering of a small group of individuals (typically 6-10) who
share common characteristics or experiences. This method encourages participants to engage in
open discussions facilitated by a skilled moderator. Focus groups offer a dynamic environment
that allows participants to interact, share their perspectives, and build upon each other’s ideas.
This method is particularly useful for exploring group dynamics, collective opinions, and societal
norms. By observing interactions within the group, researchers can gain valuable insights into

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how social influences shape individual attitudes and behaviors. Focus groups also allow for the
exploration of diverse viewpoints, enabling researchers to identify patterns, contradictions, and
shared experiences.
3. Observational Research
Observational research involves systematically observing and documenting participants’
behaviors and interactions within their natural environments. This method provides researchers
with a direct window into real-life contexts, allowing for a comprehensive understanding of social
interactions, cultural practices, and behavioral patterns. Whether conducted through participant
observation or unobtrusive observation, this method eliminates the potential biases associated
with self-reporting, as participants’ actions speak louder than words. Observational research is
especially valuable in studying nonverbal communication, contextual factors, and complex social
systems. It can also provide insights into unarticulated behaviors or experiences that may be
difficult to capture through other methods. However, careful planning, ethical considerations,
and the need for prolonged engagement are crucial for conducting successful observational
research.
4. Case Studies
Case studies involve an in-depth examination of a specific individual, group, organization, or
event. Researchers collect data through various sources, such as interviews, observations,
documents, and artifacts, to construct a holistic understanding of the case under investigation.
This method allows for an exploration of complex social phenomena in their real-life context,
uncovering rich, detailed insights that may not be accessible through other methods. Case studies
provide an opportunity to examine unique or rare cases, delve into historical contexts, and
generate context-specific knowledge. The findings from case studies are often highly detailed
and context-bound, offering rich descriptions and contributing to theory development or
refinement.
Qualitative research methods offer a range of powerful tools for exploring subjective
experiences, meanings, and interpretations. In-depth interviews allow for the exploration of
individual perspectives, while focus groups illuminate group dynamics. Observational research
provides a direct view of participants’ behaviors, and case studies offer a holistic understanding
of specific cases. By leveraging these qualitative methods, researchers can unveil deep insights,
capture complex phenomena, and generate context-specific knowledge
Qualitative Research Best Practices

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Clear Research Objectives: Clearly define the qualitative research objectives, questions, or
hypotheses that guide the study. This helps maintain focus and ensures that data collection and
analysis are aligned with the research goals.
1. Sampling Strategy:
Select participants or cases that are relevant to the qualitative research questions and provide
diverse perspectives. Purposeful sampling techniques, such as maximum variation or snowball
sampling, can help ensure the inclusion of a wide range of experiences and viewpoints.
2. Data Collection Rigor:
Employ rigorous qualitative data collection techniques to ensure the accuracy, credibility, and
depth of the findings. This may involve conducting multiple interviews or qualitative
observations, using multiple sources of data, and taking detailed field notes.
3. Ethical Considerations:
Adhere to ethical guidelines and obtain informed consent from participants. Protect the privacy,
confidentiality, and anonymity of participants and ensure their voluntary participation
throughout the qualitative research process.
4. Data Analysis:
Utilize systematic and rigorous approaches to analyze qualitative research data. This may involve
coding, categorizing, and identifying patterns or themes within the data. Software tools like
NVivo or ATLAS.ti can assist in organizing and analyzing large datasets.
5. Triangulation:
Enhance the validity and reliability of the findings by employing triangulation. Triangulation
involves using multiple data sources, methods, or researchers to corroborate and validate the
results, reducing the impact of researcher bias.
6. Member Checking:
Share the preliminary findings with participants to verify the accuracy and interpretation of their
data. Member checking allows participants to provide feedback and corrections, enhancing the
trustworthiness of the research.
7. Reflexive Journaling:

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Maintain a reflexive journal throughout the research process to record reflections, insights, and
decisions made during data collection and analysis. This journal can serve as a valuable tool for
ensuring transparency and traceability in the research process.
8. Clear and Transparent Reporting:
Present the research findings in a clear, coherent, and transparent manner. Clearly describe the
research methodology, data collection, and analysis processes. Provide rich and thick
descriptions of the findings, supported by direct quotations and examples from the data.
By following these best practices, qualitative researchers can enhance the rigor, credibility, and
trustworthiness of their research, leading to valuable and meaningful insights into the complex
phenomena under investigation.

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Topic: Comparison of Qualitative & Quantitative
Research
A research study includes the collection and analysis of data. In quantitative research, the data
are analyzed with numbers and statistics, and in qualitative research, the data analyzed are non-
numerical and perceive the meaning of social reality.
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.
Quantitative Research
Quantitative research is expressed in numbers and graphs. It is used to test or confirm theories
and assumptions. This type of research can be used to establish generalizable facts about a topic.
Common quantitative methods include experiments, observations recorded as numbers, and
surveys with closed-ended questions.

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Quantitative research is at risk for research biases including information bias, omitted variable
bias, sampling bias, or selection bias.
What Is Quantitative Research?
Quantitative research is for testing hypotheses and measuring relationships between variables.
It follows the process of objectively collecting data and analyzing it numerically, to determine and
control variables of interest. This type of research aims to test causal relationships between
variables and provide generalized results. These results determine if the theory proposed for the
research study could be accepted or rejected.
When to Use Quantitative Research?
Quantitative research is used when a research study needs to confirm or test a theory or a
hypothesis. When a research study is focused on measuring and quantifying data, using a
quantitative approach is appropriate. It is often used in fields such as economics, marketing, or
biology, where researchers are interested in studying trends and relationships between variables.
Benefits of Quantitative Research
Quantitative data is interpreted with statistical analysis. The type of statistical study is
based on the principles of mathematics and it provides a fast, focused, scientific and
relatable approach.
Quantitative research creates an ability to replicate the test and results of research. This
approach makes the data more reliable and less open to argument.
After collecting the quantitative data, expected results define which statistical tests are
applicable and results provide a quantifiable conclusion for the research hypothesis
Research with complex statistical analysis is considered valuable and impressive.
Quantitative research is associated with technical advancements like computer modeling
and data-based decisions.
Quantitative Research Example
An organization wishes to conduct a customer satisfaction (CSAT) survey by using a survey
template. From the survey, the organization can acquire quantitative data and metrics on the
brand or the organization based on the customer’s experience. Various parameters such as
product quality, pricing, customer experience, etc. could be used to generate data in the form of
numbers that is statistically analyzed.

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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.
Qualitative research is also at risk for certain research biases including the Hawthorne effect,
observer bias, recall bias, and social desirability bias.
The differences between quantitative and qualitative 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.
What Is Qualitative Research?
Qualitative research observes and describes a phenomenon to gain a deeper understanding of a
subject. It is also used to generate hypotheses for further studies. In general, qualitative research
is explanatory and helps understands how an individual perceives non-numerical data, like video,
photographs, or audio recordings. The qualitative data is collected from diary accounts or
interviews and analyzed by grounded theory or thematic analysis.
When to Use Qualitative Research?
Qualitative research is used when the outcome of the research study is to disseminate knowledge
and understand concepts, thoughts, and experiences. This type of research focuses on creating
ideas and formulating theories or hypotheses.
Benefits of Qualitative Research
Unlike quantitative research, which relies on numerical data, qualitative research relies
on data collected from interviews, observations, and written texts.
It is often used in fields such as sociology and anthropology, where the goal is to
understand complex social phenomena.
Qualitative research is considered to be more flexible and adaptive, as it is used to study
a wide range of social aspects.
Additionally, qualitative research often leads to deeper insights into the research study.
This helps researchers and scholars in designing their research methods.

38. 37
Qualitative Research Example
In research, to understand the culture of a pharmacy company, one could take an ethnographic
approach. With an experience in the company, one could gather data based on the —
Field notes with observations, and reflections on one’s experiences of the company’s
culture
Open-ended surveys for employees across all the company’s departments via email to
find out variations in culture across teams and departments
Interview sessions with employees and gather information about their experiences and
perspectives.
Qualitative Vs. Quantitative Research – A Comparison
Qualitative Research Quantitative Research
It helps understand human
behavior to find the way people
think and analyze their
experiences.
It aims to compute numbers and
perform statistical analysis.
These research methods are
ideal when there is no fixed set
of questions, and the discussion
is useful to explore issues.
It helps generate numerical data
and hard facts using statistical,
logical, and mathematical
techniques.
The time consumed for planning
is less as compared to the
analysis phase.
The time consumed for planning
is more as compared to the
analysis phase.

39. 38
Qualitative & Quantitative Research Data Collection Methods
Data collection methods
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
Quantitative research data is acquired from surveys, experiments, observations, probability
sampling, questionnaire observation, and content review. Surveys usually contain a list of
questions with multiple-choice responses relevant to the research topic under study. With the

40. 39
availability of online survey tools, researchers can conduct a web-based survey for quantitative
research.
Quantitative data is also assimilated from research experiments. While conducting experiments,
researchers focus on exploring one or more independent variables and studying their effect on
one or more dependent variables.
1. Surveys:
List of closed or multiple choice questions that is distributed to a sample (online, in person, or
over the phone).
2. Experiments:
Situation in which different types of variables are controlled and manipulated to establish cause-
and-effect relationships.
3. Observations:
Observing subjects in a natural environment where variables can’t be controlled.
Qualitative Data Collection Methods
Qualitative data is collected from interview sessions, discussions with focus groups, case studies,
and ethnography (scientific description of people and cultures with their customs and habits).
The collection methods involve understanding and interpreting social interactions.
Qualitative research data also includes respondents’ opinions and feelings, which is conducted
face-to-face mostly in focus groups. Respondents are asked open-ended questions either verbally
or through discussion among a group of people, related to the research topic implemented to
collect opinions for further research.
1. Interviews:
Asking open-ended questions verbally to respondents.
2. Focus groups:
Discussion among a group of people about a topic to gather opinions that can be used for further
research.
3. Ethnography:

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Participating in a community or organization for an extended period of time to closely observe
culture and behavior.
4. Literature review:
Survey of published works by other authors.
When to use qualitative vs. quantitative research
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.
A Step-wise Guide to Conduct Qualitative and Quantitative Research
Understand the difference between types of research — qualitative, quantitative, or
mixed-methods-based research.
Develop a research question or hypothesis. This research approach will define which type
of research one could choose.
Choose a method for data collection. Depending on the process of data collection, the
type of research could be determined.
Analyze and interpret the collected data. Based on the analyzed data, results are
reported.
If observed results are not equivalent to expected results, consider using an unbiased
research approach or choose both qualitative and quantitative research methods for
preferred results.
Research question
How satisfied are students with their studies?
1. Quantitative research approach

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You survey 300 students at your university and ask them questions such as: “on a scale from 1-5,
how satisfied are you’re with your professors?”
You can perform statistical analysis on the data and draw conclusions such as: “on average
students rated their professors 4.4”.
2. 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.
3. 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.
How to analyze qualitative and quantitative data
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.
1. 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

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The correlation or causation between two or more variables
The reliability and validity of the results
2. 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:
3. 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
4. Discourse analysis:
Studying how communication works in social contexts
Conclusion:
With an awareness of qualitative vs. quantitative research and the different data collection
methods, researchers could use one or both types of research approaches depending on their
preferred results. Moreover, to implement unbiased research and acquire meaningful insights
from the research study, it is advisable to consider both qualitative and quantitative research
methods.

44. 43
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