PSYC 6229.  Statistical modelling of perception and cognition

Department of Psychology
York University

Winter term 2018
Thursday, 11:30-2:30


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    pitman   
• Topic 2.  R programming    code    problems    solutions    jones    MATLAB-python-R    MATLAB-R  
• Topic 3.  Random variables    code    problems    solutions    pitman   
• Topic 4.  Signal detection theory    code    problems    solutions    heeger    wickens    gescheider   
• Topic 5.  Linear models in R   code    problems    solutions    dalgaard   
• Topic 6.  Model fitting   code    problems    solutions    wichmann   

Tests and problem sets

Test bank   
Problem set 1   
Problem set 2