STAT 498: Independent Study: Bayesian Methods of Data Analysis
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Vital Statistics

This is an independent study following the course materials from the special topics course STAT-489: Bayesian Methods of Data Analysis, taught in Spring 2017.

Principal Textbooks

Gelman, Carlin, Stern, Dunson, Vehtari & Rubin, Bayesian Data Analysis, Third Edition (CRC, 2013). ISBN 978-1-4398-4095-5
McElreath, Statistical Rethinking: A Bayesian Course with Examples in R and Stan, First Edition (CRC, 2017). ISBN 978-1-4822-5344-3

Supplementary Textbooks

Jaynes, Probability Theory: The Logic of Science, First Edition (Cambridge, 2003). ISBN 978-0-52-159271-0 Also available as an electronic book through the Wallace Library.
Sivia with Skilling, Data analysis: a Bayesian tutorial, Second Edition (Oxford, 2006). ISBN 978-0-1985-6832-2
Also available as an electronic book through the Wallace Library.
Kruschke, Doing Bayesian Data Analysis: A Tutorial with R, JAGS and Stan, Second Edition (Academic Press, 2014). ISBN 978-0-1240-5888-0
Also available as an electronic book through the Wallace Library.

Other Useful References

Bolstad & Curran, Introduction to Bayesian Statistics, Third Edition (Wiley, 2016). ISBN 978-1-1180-9156-2
Bolstad, Understanding Computational Bayesian Statistics, First Edition (Wiley, 2009). ISBN 978-0-4700-4609-8

Course Webpage

http://ccrg.rit.edu/~whelan/STAT-498/ (this page)

Instructor

Dr. John T. Whelan

LAC(74)-2063, 5-5083

john.whelan@astro.rit.edu or jtwsma@rit.edu

Office Hours

TR 10:00-11:50

Mailing list

discuss-statistics-whelan

Course Calendar

Refer to the course calendar for the planned trajectory through the material. See also the course calendar from STAT-489

Lecture Notes

Part One: Bayesian Parameter Estimation
- R commands from demonstrations
Part Two: Bayesian Model Evaluation
- R commands from demonstrations
Part Three: Computational Methods
- R commands from demonstrations
Part Four: Generalized Linear Models
- R commands from demonstrations
Bayesian Statistics Notes from STAT 406

Problem Sets

Problem Set 1 -- Due 2019 January 22
Problem Set 2 -- Due 2019 January 29
Problem Set 3 -- Due 2019 February 5
Problem Set 4 -- Due 2019 February 12
Problem Set 5 -- Due 2019 february 26
- data for problem 2
Problem Set 6 -- Due 2019 March 5
Problem Set 7 -- Due 2019 March 19
Problem Set 8 -- Due 2019 March 26
- JAGS model for problem 2
Problem Set 9 -- Due 2019 April 9
Problem Set 10 -- Due 2019 April 16
Problem Set 11 -- Due 2019 April 23

Webpages for Other Courses

I've taught some other courses which contained Bayesian material.

Links

Last Modified: 2019 January 17

Dr. John T. Whelan / john.whelan@astro.rit.edu / Professor, School of Mathematical Sciences & Center for Computational Relativity and Gravitation, Rochester Institute of Technology

The contents of this communication are the sole responsibility of Prof. John T. Whelan and do not necessarily represent the opinions or policies of RIT, SMS, or CCRG.

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