Real World Research by Robson

Jeffrey Chou

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Sustainable Everday

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2 min read

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Mar 2, 2019

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Basic Rules for dealing with qualitative data

1. Analysis of some form should start as soon as data is collected. Don’t allow data to accumulate without preliminary analysis.
2. Make sure you keep tabs on what you have collected (Get it indexed)
3. Generate themes, categories, codes, etc. as you go along. Start by including rather than excluding; you can combine and modify as you go on.
4. Use some form of filing system to sort your data. Be prepared to re-sort. Play with data.
5. There is no one ‘right’ way of analyzing this kind of data — which places even more emphasis on your being systematic, organized and preserving.
6. You are seeking to take apart your data in various ways and then trying to put them together again to form some consolidated picture. Your main tool is comparison.

Guidelines for coding of qualitative data

1. Coding is of categories in the data. Try to discover genuine categories and give them a (provisional) name — don’t simply precis phrases in the document or other material.
2. Relate these categories to each other, construct sub-categories where appropriate.
3. Always do this on the basis of specific data, underlining or highlighting each occurrence; reference frequently, giving page, line, etc.
4. Always do this one the basis of specific data, underlining or highlighting each occurrence; reference frequently, giving page, line, etc.
5. Develop core categories, relating all categories and sub-categories to the core.
6. Discard totally or largely unrelated categories, unless you can find some way of linking them to the core.

Drawing conclusions from qualitative data — tactics

1. Counting: Categorizing data and measuring the frequency of occurrence of the categories.
2. Patterning: Noting of recurring patterns or themes.
3. Clustering: Grouping of objects, persons, activities, setting, etc. with similar characteristics.
4. Factoring: Grouping of variables into a small number of hypothetical factors.
5. Relating variables: Discovery of the type of relationship (if any) between two or more variables.
6. Building of causal networks: Development of chains or webs of linkages between variables.
7. Relating findings to general theoretical frameworks: Attempt to find general propositions that account for the particular findings in this study.