Statistics for Linguists: An Introduction Using R is the first statistics textbook on linear models for linguistics. The book covers simple uses of linear models through generalized models to more advanced approaches, maintaining its focus on conceptual issues and avoiding excessive mathematical details. It contains many applied examples using the R statistical programming environment. Written in an accessible tone and style, this text is the ideal main resource for graduate and advanced undergraduate students of Linguistics statistics courses as well as those in other fields, including Psychology, Cognitive Science, and Data Science.

chapter 1|26 pages

Introduction to R

chapter 2|26 pages

The Tidyverse and Reproducible R Workflows

chapter 4|17 pages

Introduction to the Linear Model

Simple Linear Regression

chapter 6|14 pages

Multiple Regression

chapter 7|16 pages

Categorical Predictors

chapter 8|24 pages

Interactions and Nonlinear Effects

chapter 9|14 pages

Inferential Statistics 1

Significance Testing

chapter 11|18 pages

Inferential Statistics 3

Significance Testing in a Regression Context

chapter 12|20 pages

Generalized Linear Models 1

Logistic Regression

chapter 13|14 pages

Generalized Linear Models 2

Poisson Regression

chapter 14|13 pages

Mixed Models 1

Conceptual Introduction

chapter 15|29 pages

Mixed Models 2

Extended Example, Significance Testing, Convergence Issues

chapter 16|7 pages

Outlook and Strategies for Model Building