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Statistical Advisor, How To Compare Two Variables

General Comparison (Nonparametrics)


NONPARAMETRICS & DISTRIBUTIONS: This chapter discusses several so-called nonparametric tests for comparing variables. Compared to parametric tests (t-test, ANOVA), nonparametric tests are based on less restrictive assumptions about the nature and distribution of the variables in the comparisons. For example, there are several tests for variables containing only rank order information. Such data may arise, if one asks respondents in a consumer survey to rank order their preferences for several competing brands of soap.

The NONPARAMETRICS & DISTRIBUTIONS chapter also describes the McNemar test for changes in proportions. Such data may, for example, arise if one wants to compare how many students in a class fail a particular test at the beginning of the semester, and at the end of the semester.

GRAPHICAL ANALYTIC TECHNIQUES: Graphical analytic techniues include numerous facilities for producing histograms, line graphs, scatterplots, etc., simultaneously for more than one variable. These graphs offer a wide variety of methods to visualize differences between variables.