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