ABSTRACT
Chapter 3 addresses techniques to test whether categorical variables influence metric variables; for instance, can gender influence income? Initially, it presents the t-test, suitable in cases when the qualitative variable has only two categories. ANOVA comes next, which is appropriate for variables with more than two categories. Additionally, the interactions effects are presented, situations when two or more categorical variables are combined to test their joined influence. For instance, if marital status has an effect on expense, could it be affected (decreased or increased) by an effect coming from gender? Lastly, the chapter presents MANOVA, which deals with more than one dependent metric variable; for example, can educational level influence traveling, clothing, and reading preferences? Each technique contains a theoretical description, followed by an example with the SPSS commands and the results tables with comments. The chapter also includes exercises, such as a road map to perform the analysis, an interpretative exercise with results tables, and a market context to guide a research design.
