Data analysis and interpretation

Data analysis and interpretation

1. research involves summarizing data

2. attempt by the researcher

3. Researchers think about and develop hunches

4. on two questions:

   • Is your research question still answerable and worth answering?
   • Are your data collection techniques catching the kind of data you want and filtering out the data that you don’t want?

5. Steps in analyzing qualitative research data

   • Qualitative data analysis is a cyclical
   • Reading/memoing
     • important during the initial reading of narrative data.
   • Describing
     • developing thorough and comprehensive descriptions
   • Classifying
     • find connections among the data.

6. Data analysis strategies

   • computer programs are available
   • using matrixes, charts, concept maps, graphs, and figures
   • Coding
     • the process of marking units
   • Asking key questions
     • strategy that involves the researcher
   • Concept mapping
     • create a visual display of the major influences

7. Data interpretation strategies

   • is based heavily on the connections
   • Extending the analysis
     • data interpretation strategy
       • researcher raises questions about the study
   • Contextualizing
     • literature involves using the review of related literature
   • Provide
     • clear link among data collection, analysis, and interpretation.

8. Ensuring credibility in your study

   • check the credibility
     • six questions
       • Are the data based on one’s own observation or on hearsay?
       • Are observations corroborated by others?
       • In what circumstances was an observation made or reported?
       • How reliable are those providing the data?
       • What motivations may have influenced a participant’s report?
       • What biases may have influenced how an observation was made or reported?