Preface. Statistical Foundations. Binary Results – Single Samples and 2 x 2 Tables. Continuous Variables – One and Two Samples. The Linear Model – Continuous Regressor Variables. The Linear Model – Discrete Regressor Variables. The Linear Model – Random Effects and Mixed Models. Polytomous Discrete Variables – R x C Contingency Tables. The Generalized Linear Model – Logistic Regression. Multivariate Continuous Variables – Dimension Reduction. Multivariate Continuous Variables – Grouping and Discrimination. Bayesian and Frequentist Philosophies. Decision and Game Theory – Bayesian and Non-Bayesian. Some Notes on Sample Size Estimation.