This book aims to provide a practical extension of introductory statistics typically taught in psychology into the general linear model (GLM) using R.
Typically, introductory univariate statistics courses in psychology cover the following inferential analyses (plus or minus a few more analyses):
- One Sample t-test
- Dependent Samples t-test
- Independent Samples t-test
- One-Way Analysis of Variance (ANOVA)
- Factorial ANOVA
- Correlation
- Simple Linear Regression
These conventions may be useful for quickly talking about a particular statistical analysis with others; however, thinking of these analyses as derivatives (or special cases) of the GLM (i.e., ordinary least squares [OLS] regression) lends itself to understanding more advanced statistical techniques. Given that, the book will provide some evidence along with R code for others to see how the aforementioned analyses can be analyzed within the GLM framework with identical answers. The GLM is not a new idea, but an idea that needs emphasizing.
This book is meant to be an live open-source book that can be edited by us and others (you) in perpetuity by creating issues or pull requests on github.