Bayesian Cognitive Modeling

Michael D. Lee, Eric-Jan Wagenmakers

ISBN 10: 1107603579 / ISBN 13: 9781107603578

Published by Cambridge University Press, GB, 2014

About this Item

Bayesian inference has become a standard method of analysis in many fields of science. Students and researchers in experimental psychology and cognitive science, however, have failed to take full advantage of the new and exciting possibilities that the Bayesian approach affords. Ideal for teaching and self study, this book demonstrates how to do Bayesian modeling. Short, to-the-point chapters offer examples, exercises, and computer code (using WinBUGS or JAGS, and supported by Matlab and R), with additional support available online. No advance knowledge of statistics is required and, from the very start, readers are encouraged to apply and adjust Bayesian analyses by themselves. The book contains a series of chapters on parameter estimation and model selection, followed by detailed case studies from cognitive science. After working through this book, readers should be able to build their own Bayesian models, apply the models to their own data, and draw their own conclusions.

Seller Inventory # LU-9781107603578

Bibliographic Details

• Title: Bayesian Cognitive Modeling
• Publisher: Cambridge University Press, GB
• Publication Date: 2014
• Language: English
• ISBN 10: 1107603579
• ISBN 13: 9781107603578
• Binding: Paperback
• Condition: New
• Dimensions: 18.9W x 1.63H x 24.61D centimeters 18.9 centimeters width by 1.63 centimeters height by 24.61 centimeters depth
• Weight: 550 grams

About this title

Synopsis

Bayesian inference has become a standard method of analysis in many fields of science. Students and researchers in experimental psychology and cognitive science, however, have failed to take full advantage of the new and exciting possibilities that the Bayesian approach affords. Ideal for teaching and self study, this book demonstrates how to do Bayesian modeling. Short, to-the-point chapters offer examples, exercises, and computer code (using WinBUGS or JAGS, and supported by Matlab and R), with additional support available online. No advance knowledge of statistics is required and, from the very start, readers are encouraged to apply and adjust Bayesian analyses by themselves. The book contains a series of chapters on parameter estimation and model selection, followed by detailed case studies from cognitive science. After working through this book, readers should be able to build their own Bayesian models, apply the models to their own data, and draw their own conclusions.

About the Authors

Michael D. Lee is a professor in the Department of Cognitive Sciences at the University of California, Irvine.

Eric-Jan Wagenmakers is a professor in the Department of Psychological Methods at the University of Amsterdam.