Aspect
Qualitative Research
Quantitative Research
Definition
Explores experiences, meanings, and interpretations.
Measures relationships between variables using numerical data.
Purpose
Understanding deep insights, motivations, and perspectives.
Testing hypotheses, measuring variables, and identifying patterns.
Nature of Data
Non-numerical (words, images, observations).
Research Approach Inductive (builds theories from data).
Numerical (statistics, measurements, scores).
Deductive (tests theories using data).
Mixed-Methods Research
Combines qualitative and quantitative methods for a
comprehensive understanding.
Providing a broader and deeper analysis by
integrating different types of data.
Both non-numerical and numerical data.
Uses both inductive and deductive approaches.
Research Methods
- Phenomenology
- Ethnography
- Case Study
- Grounded Theory
- Narrative Research
- Experimental
- Quasi-Experimental
- Correlational
- Descriptive
- Convergent (simultaneous data collection)
- Explanatory Sequential (quant → qual)
- Exploratory Sequential (qual → quant)
Data Collection
- Interviews (structured, semi-structured, unstructured)
- Focus Groups
- Observations
- Document Analysis
- Surveys & Questionnaires
- Experiments
- Structured Observations
Uses a combination of qualitative and quantitative
data collection methods.
Sampling
- Purposive Sampling (choosing relevant participants)
- Snowball Sampling (referrals)
- Random Sampling (equal selection chance)
- Stratified Sampling (dividing into subgroups)
- Systematic Sampling (every nth participant)
Uses either concurrent or sequential sampling
strategies.
Data Analysis
- Thematic Analysis (finding patterns)
- Content Analysis (categorizing data)
- Descriptive Statistics (mean, median, mode)
- Inferential Statistics (t-tests, ANOVA, regression)
Merging, connecting, or embedding both qualitative
and quantitative analyses.
Reliability & Validity
- Trustworthiness ensured through triangulation, member
checking, and reflexivity.
- Reliability ensured through Cronbach’s Alpha, test-retest reliability. Ensures credibility by cross-validating findings from
- Validity ensured through construct validity, statistical controls.
different data sources.
Ethical
Considerations
Informed consent, confidentiality, researcher reflexivity.
Informed consent, anonymity, minimizing risks.
Addresses ethical concerns from both qualitative and
quantitative perspectives.
Limitations
- Subjective interpretation
- Limited generalizability
- Time-consuming analysis
- May oversimplify complex phenomena
- Limited contextual depth
- Requires large samples
- Complex data collection and analysis
- Requires expertise in both methods
- Time and resource-intensive
Strengths
- Provides deep understanding
- Captures rich details
- Flexible and adaptive
- Generalizable results
- Statistical rigor
- Replicable and objective
- Comprehensive understanding
- Balances depth and breadth
- Triangulates findings for more reliable results
Best Used For
- Exploring new topics
- Understanding human experiences
- Studying cultural and social interactions
- Testing hypotheses
- Measuring variables
- Establishing cause-effect relationships
- When a single method is insufficient
- Bridging numerical trends with human insights
- Validating findings through multiple approaches