|Contact:||Jianyu Wang firstname.lastname@example.org|
|Class Time:||11:15-12:30 WH 005|
|Class Days:||Tu, Th|
|Sequence:||No specific sequence.|
|Pre-Requisites:||Two courses at the graduate level or consent by the instructor. A course equivalent to MATH-M 463 (Introduction to Probability Theory) is ideal.|
|Algebra Required:||Some preliminary knowledge of matrix algebra is needed to discuss some ideas about performing regression analysis from a Bayesian point-of-view.|
|Calculus Required:||Some notions of integration are needed. Specially dealing with integrals that arise from working with known probability distributions. Some basic knowledge of differentiation is needed too.|
|Contact Person for Authorization:||Two statistics courses at the graduate level; otherwise, permission of instructor.|
|Recommended follow-up classes:||Any topics course in advanced statistical methods that involve some form of Bayesian methodology.|
|Syllabus:||No Syllabus Avaliable|
|Keywords:||Prior and posterior distributions, Bayes theorem, model formulation, Bayesian computation, model checking and sensitivity analysis.|
|Description:||The course covers an introduction to the theory and practice of Bayesian inference. Topics covered include: Prior and posterior distributions, Bayes theorem, model formulation, Bayesian computation, model checking and sensitivity analysis. This is a general class on Bayesian methods. Some basic knowledge of probability distributions, calculus and linear algebra is assumed.|
*Hoff, Peter (2009) "A first Course in Bayesian Statistical Methods". New York: Springer. ISBN 978-0-387-92299-7.
*Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., Rubin, D. B. (2003), Bayesian data analysis, Second Edition, Chapman and Hall/CRC. ISBN 978-1-4398-4095-5.
*Marin, J. M. and Robert, C. (2007), Bayesian Core: A Practical Approach to Computational Bayesian Statistics. New York: Springer. ISBN 978-0-387-38979-0.
|Substantive Orientation:||This course accommodates students from a variety of disciplines. In past semesters, S626 has been attended by students in Statistics, Computer Science, Economics, Biological Sciences, and Political Science, among others.|
|Applied/Theoretical:||Historically this course had a theoretical focus. This semester we are pursuing more of a balance between theory and practice.|
|Formal Computing Lab:||No|
|How Software is Used:||The software is mainly used for computation and data analysis for in-class examples and homework assignments. Only a reasonably low level of programming is required for both R and Winbugs.|
|Problem Sets:||In the range of 5-6 homeworks a semester|
|Data Analysis:||Yes, typically involving actual data sets. Examples of proportions, count data and estimation of rates are considered. Along with some regression models.|
|Exams:||Historically, a midterm test and a final exam.|