Spring 2026

Instructors: Adam Albright, Edward Flemming

Lecture: W 10am–1pm, 32-D461

Description:

The field of phonology has increasingly looked to experimental results to confirm and extend its understanding of phonological patterns. In this course, we will examine some of the issues involved in deriving experimentally testable predictions from a theory, designing and running an experiment, and interpreting the results.

The class has several goals:

Consider the relation between linguistic theory, empirical predictions, and experimental results
Gain practical knowledge in designing and carrying out experiments in the lab and on-line, and performing data analysis using R
Gain familiarity with some commonly used experimental paradigms, comparing what they can tell us about the linguistic system

The emphasis this year will be on statistical analysis. The course will be organized around the statistical models that are most applicable to linguistic experiments:

Linear models and linear mixed-effects models
Generalized linear (mixed) models: logistic/probit regression, ordinal logistic regression, log-linear models
Factor coding for interpretable statistical analysis
Possibly: Bayesian linear models

The application of these models will be illustrated through case studies selected based on the interests of the participants. Candidates include: Coarticulation, perceptual similarity, the P-Map Hypothesis, statistics of the lexicon, wug/blick tests and Universal Grammar/learning biases. Experimental paradigms examined are likely to include production, perceptual identification and discrimination, artificial language learning, and acceptability judgments.