ABSTRACT

To understand the information in this chapter, it is necessary to remember or to review the sections in Chapter 1 about variables and Chapter 3 about levels of measurement (nominal, dichotomous, ordinal, and normal/scale). It is also necessary to remember the distinction we made between difference and associational research questions and between descriptive and inferential statistics. This chapter focuses on inferential statistics, which, as the name implies, refers to statistics that make inferences about population values based on the sample data that you have collected and analyzed. What we call difference inferential statistics lead to inferences about the differences (usually mean differences) between groups in the populations from which the samples were drawn. Associational inferential statistics lead to inferences about the association or relationship between variables in the population. Thus, the purpose of inferential statistics is to enable the researcher to make generalizations beyond the specific sample data. Before we describe how to select statistics, we introduce design classifications.