ABSTRACT
This chapter introduces some of the fundamental principles of linear regression. It focuses on a statistical technique known as linear regression as a means of exploiting that information and using it to test hypotheses. Linear regression is a means of estimating the value of a quantitative outcome variable from another quantitative or dichotomous variable by using information about the relationship between the two. So linear regression gives us a new way of conceptualizing deviation and difference—as differences from what would be predicted from knowledge about a variable related to the outcome. As computers have gotten faster, tests based on data permutation are being discussed and recommended more and more often. For a discussion of permutation tests in greater detail, see Edgington and Lunneborg. On the surface it might seem like a permutation test of random association is practically infeasible.
