Bayesian Statistical Methods
MWF, 9:30-10:20, EEB 054
Th, 12:30-1:20, Communications B027
- Peter Hoff
- C-319 Padelford
- Office Hours: Tue 9:30-10:30, Wed 10:30-11:30 or by appointment.
- pdhoff at uw dot edu
Please include "564" (without quotes) in any emails to allow for appropriate filtering.
- Alex Volfovsky
- B-228 Padelford
- Office Hour: TBA
- volf at uw dot edu
- Week 10: Read Chapter 10 and do the final homework.
- Week 9: Read Chapter 9 and do exercises 9.2(a) and all of 9.3, to be turned in Friday June 3.
- Week 8: Read Chapter 8 and do exercises 8.1 and 8.3, to be turned in
Friday May 27.
- Week 7: Read Chapter 7 and do exercises 7.4 and 7.6. For 7.4 part d, only do d.iii to be turned in Friday May 20.
- Week 6: Read Chapter 6 and do these exercises to be turned in Friday May 13.
- Week 5: Read Chapter 5 and do exercises 4.8 and 5.1 and 5.2 to be turned in Friday May 6.
- Week 4: Read Chapter 4 and do exercises 3.3 part (a), 4.1 and 4.2, to be turned in Wednesday April 27. For 4.2 (b) use n0 values between 1 and 10. For 4.2 (c2) you only have to repeat part 4.2 (a) using the predictive distribution.
- Week 3: Read Chapter 3 and and do exercises 3.2, 3.7 and 3.9, to be turned in Wednesday April 20.
- Week 2:
- Week 1:
Read Chapter 1 and start Chapter 2 of the text.
Each quiz will be given the same weight as a homework. There will be the opportu
to correct quiz mistakes for partial credit.
- Eight or nine homework assignments
- Two or three in-class quizzes, which will be announced in advance
Additionally, we will cover the basics of
Monte-Carlo integration and Markov chain Monte Carlo
(Gibbs sampling and the Metropolis-Hastings algorithm).
This material will be covered concurrently with
the material listed above.
- Concepts of randomness and probability
- Review of probability calculus
- Inference for binomial, Poisson and normal distributions
- Hierarchical models
- Multivariate normal distribution
- Linear regression models
- Generalized linear models
- Generalized linear mixed-effects models
Each turned in item receives an initial grade of
x, then the actual grade is y=x exp(-d/8), where d is
the number of days (including weekends) after the due date I receive the work.
Everyone receives one grace day to be applied to
one homework for the entire quarter.