Psychology & Brain Sciences 891C - S-Modeling Behavior

The goals of this course are to demonstrate first, what mathematical models of behavior are and how to evaluate them in a research context, and second, the basics behind a number of common modeling techniques and how to implement them. The course will begin with an overview of mathematical modeling and a discussion of the role of mathematics for understanding behavioral data. Rather than focusing on theory, the emphasis of the rest of the course will be on evaluation and applications of and hands-on experience with particular modeling techniques. Possible topics include: multinomial models, models of choice, models of subjective sensation, signal detection, stimulus sampling theory, Markov models, random walk and diffusion models, multidimensional scaling, model selection, Bayesian models, ACT-R, connectionist models and dynamic systems. Students will be assigned weekly readings, mini-projects and a larger group project. Although there are no course prerequisites, basic algebra skills, elementary programming and undergraduate statistics would be helpful.

PSYCH,LING,SOM,COMDIS,NBS,PHIL