Textbook and Grading | AMS207, Spring 16, Section 01

Bayesian Data Analysis, Third Edition. A. Gelman, J. B. Carlin, H. S. Stern, D.B. Dunson, A. Vehtari and D. B. Rubin. Chapman and Hall/CRC.

Bayesian Ideas and Data Analysis, Ronald Christensen, Wesley Johnson, Adam Branscum, and Timothy Hanson, Chapman and Hall/CRC
Bayesian Computation with R, Jim Albert, Springer
Markov Chain Monte Carlo - Stochastic Simulation for Bayesian Inference, Second Edition, Dani Gamerman and Hedibert Lopes, Chapman and Hall/CRC
Bayesian Methods for Data Analysis, Third Edition, Brad Carlin and Thomas Louis, CRC Press
Monte Carlo Statistical Methods, Second Edition, Christian Robert and George Casella

Grading: There will be one midterm (45%, 05/10/16), and two quizzes (25%, 04/19/16; 30%, 05/31/16). Exams and quizzes will be based on the homework. They will usually have two parts: one to be taken in class and one to take home. The take home part will involve the analysis of a case study and/or the application of some methods taken from an article published in one of the leading statistical journals. You will have to turn in a pdf file obtained by using the latex template based on the the ASA class
Homework: There will be periodical homework which will not be graded. Homework will give a very close indication of the material that will be covered in exams and quizzes. Some of the homework will involve numerical exercises.
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