Richard Murray
  Centre for Vision Research
  York University

PSYC 6229.  Statistical modelling of perception and cognition

Department of Psychology
York University

Winter term 2016
Tuesday and Thursday, 11:30-1:00


General description:  This graduate course covers fundamental statistical concepts and their application to statistical modelling in psychology. Topics in statistical foundations include probability, random variables, common statistical distributions, and Bayes' theorem. To illustrate these concepts we cover classic statistical models of behaviour and physiology, such as signal detection theory, optimal cue combination, diffusion models of reaction times, probability summation, and ideal observers. We also discuss model fitting and testing, e.g., parameter estimation, bootstrapping, goodness of fit, and model selection. The course uses R, a statistical programming language, for illustrations and problems.

Lecture notes

• Topic 1.  Probability      problems    solutions   
• Topic 2.  Data structures in R    code    problems    solutions    MATLAB-R   MATLAB-Python-R   
• Topic 3.  Calculus    code    problems    solutions    calculus notes   
• Topic 4.  More programming in R    code    problems    solutions   
• Topic 5.  Random variables    code    problems    solutions   
• Topic 6.  Signal detection theory    code    problems    solutions    Wickens   Gescheider   
• Topic 7.  Cue combination    code    problems    solutions    Alais   
• Topic 8.  Maximum likelihood    code    problems    solutions   
• Topic 9.  The general linear model    code    problems    solutions   
• Topic 10.  Ideal observers    code    problems    solutions    Geisler   
• Topic 11.  Model testing    code    problems    solutions    Wichmann   

Tests and problem sets

Test bank   
Problem set 1    solutions   
Problem set 2    solutions