An accessible course in statistics using STATISTICA PL with medical examples. Volumes 1–3

Volume 1: Basic statistics

The examples, issues and empirical data presented make this volume especially appealing to professionals in biomedical sciences. The author draws on his many years of experience in analyzing data from this field and teaching statistics courses.

Volume 2: Linear and nonlinear models

In this volume, the author aims to introduce readers to more advanced methods of statistical analysis related to modeling relationships between variables. It begins with classical regression analysis techniques, residual analysis and model building. Then, the author addresses the topic of nonlinear regression. A separate chapter is dedicated to logistic regression. However, the most space is devoted to analysis of variance.

Volume 3: Multivariate analyses

In writing the final volume, the author set out to present selected methods of multivariate statistical data analysis that, in his opinion, are most frequently used in the processing of biomedical research results. These methods allow for the analysis of phenomena described by many variables. The first technique discussed is canonical correlation analysis, which examines the relationships between two sets of variables and can be seen as an extension of multiple regression analysis. Next, the author covers discriminant analysis, which makes it possible to find rules for assigning objects described by multiple variables to predefined groups based on a linear discriminant function.