About

This site contains materials for Statistical Methods in Linguistics, a course taught by Aaron Steven White at the University of Rochester.

Course documents

• Syllabus
• Final project rubric

About the course

The course develops the probability-theoretic and statistical tools used to analyze linguistic data. We begin by asking how linguistic observations can be represented as outcomes in a probability space; we then develop random variables and probability distributions; finally, we use those objects to motivate frequentist and Bayesian inference, regression, generalized linear models, and mixed-effects models.

The notes are organized by topic rather than class meeting. Each substantive page introduces one principal concept and uses only earlier prerequisites. The chapter dependency graph shows which chapters supply concepts used in later chapters.

Prerequisites

The course assumes an introductory background in linguistics. Familiarity with R or Python is useful, though the mathematical objects are introduced before they are implemented. The code is visible throughout the notes; execution is disabled in the website build because the original examples draw on several language-specific data sets and modeling environments.

Using the notes

Begin with the chapter dependency graph, use the sidebar to move among topics, and use search to locate a definition, distribution, or model.