ABSTRACT
This chapter covers bivariate analysis and issues related to linear regression and correlation. It outlines the different goals behind regression and correlation, and it discusses the calculation of correlation coefficients, such as Pearson’s r, as well as probability values based on these. This chapter also discusses how to determine if one’s data are suitable for linear regression and correlation analyses, and it offers some alternative methods, such as generalized linear modeling (GLM), for situations in which the assumptions of standard regression and correlation are violated.
