There is no right process of analyzing the qualitative data but some steps which are followed by most of the analyst are given below:
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- Data display
- Drawing conclusions
1. Data Reduction
- This step involves filtering, focusing, simplifying, and organizing the raw data.
- The goal is to remove irrelevant information and highlight key points or patterns.
- Methods can include coding, summarizing, or categorizing the data.
Example: From 50 interview transcripts, the researcher identifies and codes only the statements related to “student stress” while ignoring unrelated comments.
2. Data Display
- After reducing the data, it is organized in a way that makes patterns and relationships visible.
- Common formats include:
- Tables and charts
- Concept maps or diagrams
- Matrices showing connections between themes
Example: A table showing how often different stress factors (“peer pressure,” “exam anxiety,” “time management”) appeared in the interviews.
3. Drawing Conclusions
- The final step is interpreting the displayed data to make sense of it.
- Analysts look for trends, patterns, relationships, and insights.
- These conclusions may also be used to formulate theories or recommendations.
Example: Concluding that “time management issues are the most common cause of stress among students,” which can guide interventions or further research.