Preface

This book contains the course notes for Psych 252. The book is not intended to be self-explanatory and instead should be used in combination with the course lectures posted here.

If you have any questions about the notes, please feel free to contact me at: or post an issue on the book’s github repository.

Course description

This course offers an introduction to advanced topics in statistics with the focus of understanding data in the behavioral and social sciences. It is a practical course in which learning statistical concepts and building models in R go hand in hand. The course is organized into three parts: In the first part, we will learn how to visualize, wrangle, and simulate data in R. In the second part, we will cover topics in frequentist statistics (such as multiple regression, logistic regression, and mixed effects models) using the general linear model as an organizing framework. We will learn how to compare models using simulation methods such as bootstrapping and cross-validation. In the third part, we will focus on Bayesian data analysis as an alternative framework for answering statistical questions.

Course homepage

https://psych252.github.io/

License and citation

This book is licensed under the Creative Commons Zero v1.0 Universal license. If you find these materials helpful for your work, I’d appreciate you citing the book:

@book{gerstenberg2022methods,
  title = {Statistical methods for the behavioral and social sciences},
  author = {Tobias Gerstenberg},
  year = {2022},
  url = {https://psych252.github.io/psych252book/}
}