Linguistics - Modeling for Language Science

Catalog description

By the end of this course, students will be able to run mixed-effects models on data from linguistic studies, to identify appropriate analyses for new datasets, and to read and understand literature about issues related to statistical modeling. The course is divided into three units: first, students will learn the basics of programming and become comfortable solving problems with R; then, students will learn the fundamentals of regression analysis and how to understand the meanings of regression coefficients by interpreting them within a regression formula; and finally, students extend these concepts to run mixed-effects regression models in R. Throughout the course, students will practice analyses on their own and each other’s real datasets. By the end of the course, students will have compiled a portfolio of R scripts they have written and analyses they have run. (Same as SPLH 721.) Prerequisite: Graduate-level course in statistics, or consent of instructor.