Fundamentals of Data Analysis - Measuring Association—a Recap

Fundamentals of Data Analysis - Measuring Association—a Recap

A basic procedure in data analysis is determining whether or not two variables are associated. Three methods for exploring association have just been presented. Which is used depends on the nature of the variables involved. Figure 13-5 summarizes the methods of measuring association. If both of the variables are nominally scaled—in that they serve to label or identify categories such as heavy users, light users, or nonusers—then the approach is cross-tabulation. If one of the variables is intervally scaled, such as age or income (that is, scales objects and has a constant unit of measurement), then the difference between means is employed. If both variables are intervally scaled, then the appropriate association measure is the sample correlation.

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