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Emil Pulido on Qualitative Research: Analyzing Qualitative Data
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Emil Pulido on Qualitative Research: Analyzing Qualitative Data

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Qualitative research differs from Quantitative research. How does one analyze quantitative data?

Qualitative research differs from Quantitative research. How does one analyze quantitative data?

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  • 1. Qualitative Research: Data Analysis and Interpretation Guess what? There are no formulae or steps for analysing and interpreting Qualitative Research data
  • 2. However, here are some suggestions to use most of your data
    • First, data analysis is our attempt to summarize collected data in a dependable and accurate manner
    • Secondly, data interpretation is our attempt to find meaning in the data, or making sense of the data
  • 3. When analysing and interpreting qualitative data:
    • Challenge yourself to explore every possible angle and try to find patterns and seek out new understandings among the data
  • 4. Suggested steps to analyzing qualitative research data:
    • 1. become familiar with the data and identify potential themes (reading/memoing)
    • 2. examine the data in depth to provide descriptions of the setting, participant and activity (describing)
    • 3.categorize and code pieces of data and group them into themes (classifying)
  • 5. Remember it is your ability to:
    • Think
    • Imagine
    • Create
    • Intuit
    • Analyze
    • … that guides the data analysis
  • 6. Strategies that are used to analyze qualitative data:
    • 1. Identify themes
    • 2. Code your data
    • 3. Ask key questions
    • 4. Do an organizational review
    • 5. Do concept mapping
    • 6. Analyze antecedents and consequences
    • 7. Display findings
    • 8. Be honest- State what’s missing
  • 7. Yes, there are computer software that assist with data analysis
    • 1. NVivo 2.0
    • 2. The Ethnography
    • 3. HyperRESEARCH
    • 4. NUD*IST 6
  • 8. These software help - they don’t do the work or replace your abilities
    • To think
    • Summarize
    • Analyze
    • Infer
    • *Perhaps, they are most helpful in storing, helping you to manipulate and retrieving data
  • 9. Strategies for Data Interpretation:
    • 1. Extend the analysis- question your study
    • 2. Connect findings with personal experiences
    • 3. Seek advice from “critical” friends
    • 4. Contextualize findings in the literature
  • 10.
    • 5. Turn to theory as a means to: link to broader issues, move away from a purely descriptive account, and providing a rational for your work
    • 6. Know when to offer an interpretation from the data
    • Note: it is rare for qualitative researchers to use all of their data for the task is to identify important themes or meanings, not necessarily including every theme
  • 11. To ensure credibility ask:
    • 1. Are the data based on observation or hearsay?
    • 2. Is there corroboration by others for the observations?
    • 3. Within what context was the observation made or reported?
  • 12.
    • 4. How reliable were the people providing the data?
    • 5. What motivations might have influenced a participant’s report?
    • 6. What biases might have influenced how an observation was made or reported?
  • 13. Lastly, as a qualitative researcher you should:
    • Share your interpretations wisely
    • Avoid being evangelical
    • Provide a clear link between data collection, analysis, and interpretation

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