Applied Statistical Analysis for Psychology and Human Factors in R: A Graduate Course

Chapter 1: Introduction

This chapter covers the basics of why you might want to use R, the different aspects of the RStudio interface, and some basic exercises in math that expose you to numbers, operators, functions, and the like.

Chapter 7: Random Variables, Probability, Parameter estimation

This chapter provides a brief refresher on probability theory, random variables, and inferential statistics. It includes examples of estimating parameters using R functions.

This chapter covers basics of linear regression in R, with a focus on estimating parameters of a linear model using eyeball, least-squares, and quantile regression approaches.

This chapter covers methods for testing linear regression models, focusing on the logic of doing t-tests to examine linear coefficients. Also, examines Bayes factor regression, using categorical predictors, and factor:continuous predictor interactions.