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Home arrow Environment arrow Research Methods in Anthropology: Qualitative and Quantitative Approaches
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ABOUT SKILLS IN DATA ANALYSIS

We could begin our tour of data analysis anywhere, with any kind of data, because all data analysis, whether we're talking about the qualitative or quantitative kind, requires the same set of big skills. Here's a list of those big skills: (1) logical reasoning; (2) ways to test the results of logical reasoning. That's it. That's the whole list of big skills. All the other skills (and there are hundreds of them) are in one of the two big-skill categories.

The ability to engage in constant comparison, for example, is a really nice skill to develop. It's part of the logical-reasoning set of tools and it means being able to hold some ideas in your head so you can compare them to new ones that emerge as you analyze data. For qualitative data, this means holding on to themes in some narratives and comparing them to new themes that pop into your head as you read the narratives a second and a third and a fourth time. For quantitative data, constant comparison means looking for patterns in many small findings as you run, say, correlations or chi-squared tests to examine hypotheses about what goes with what.

The point is, any skills you learn about how to analyze any data—qualitative or quantitative—are going to serve you well as you work with more and different kinds of data. In fact, having lots of skills in analyzing data will make you fearless about collecting different kinds of data. Once you master multidimensional scaling and cluster analysis, for example—two methods of analysis we'll cover in this chapter—you'll be able to analyze network data and once you can do that, you can do semantic network analysis, which will dramatically extend your capacity to analyze text, and . . . you get the idea (appendix E).

tions) are very well defined, but things that mothers do (and things that people might do on a weekend, and things that you can do to stay healthy) are much less well-defined cultural domains. Many of the most interesting domains are things that people don’t have easy lists for.

 
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