Indiana University Bloomington

Psychological and Brain Science P533
Bayesian Data Analysis

Contact: John Kruschke (kruschke@indiana.edu)
Offered: Spring, Every Year
Capacity: 40
Pre-Requisites: No specific pre-requisites.
Algebra Required: No matrix algebra used.
Calculus Required: Calculus is not needed for assignments; is used on rare occasions for concepts and explanations.
Contact Person for Authorization: None.
Instructor: John Kruschke
Days Per Week Offered: TR
Website: http://www.indiana.edu/~jkkteach/P533/
Syllabus: No Syllabus Avaliable
Keywords: Bayesian, proportions, means, analysis of variance, regression, logistic, ordinal, probit, categorical
Description: Please see web page, http://www.indiana.edu/~jkkteach/P533/
Books: Kruschke, J. K. (2015). Doing Bayesian Data Analysis, 2nd Edition: A Tutorial with R, JAGS, and Stan. Academic Press. https://sites.google.com/site/doingbayesiandataanalysis/
Substantive Orientation: Any.
Statistical Orientation: Bayesian, all models.
Applied/Theoretical: Applied with thorough explanations.
Software: R
How Software is Used: For data analysis. Students also modify programs to adapt to different applications.
Problem Sets: Weekly.
Data Analysis: As part of assignments.
Presentation: None.
Exams: None.
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