This book, introduces readers into the General Linear Model (GLM). The book is a primer. That is, the introduction is brief and compact. Topics covered are conceptual, but illustrated with real-world data examples. The topics include the GLM itself, parameter estimation, correlation and regression, and analysis of variance. These, multivariate analysis of variance, and repeated measures analysis are standard topics of discussions of the GLM. This applies as well to the analysis with covariates and variable selection. Most important, this primer is the first to provide an introduction to direction dependence analysis - a method that allows one to test hypotheses of causality in observational data and to statistically determine which variables are on the dependent and which are on the independent variable sides of a model.