In Chapter 1 we discussed briefly the four types of variables that one generally encounters in empirical analysis: These are: ratio scale, interval scale, ordinal scale, and nominal scale. The types of variables that we have encountered in the preceding chapters were essentially ratio scale. But this should not give the impression that regression models can deal only with ratio scale variables. Regression models can also handle other types of variables mentioned previously. In this chapter, we consider models that may involve not only ratio scale variables but also nominal scale variables. Such variables are also known as indicator variables, categorical variables, qualitative variables, or dummy variables.1
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