PubH 8442 Bayes Decision Theory and Data Analysis- Spring 2018

Syllabus and Course Information

Click on address to send email

Instructor:

Eric Lock

elock@umn.edu

Teaching Assistant:

Jin Jin

jinxx493@umn.edu

Classroom: Moos 1-435. Class time: Mon/Wed, 9:45am-11am

Office hours for Eric Lock: Mondays 2:00pm-3pm, Wednesday 11:15-noon in Mayo A467

Office hours for Jin Jin: Thursdays 2:30pm-3:30pm in Mayo A446


 

Class feed:

1/17.Slides: Course introduction; Bayes' rule and Bayesian probability;
Reading: Carlin & Louis, Chap 1; NY Times Bayesian article
1/22. Slides: Prior and posterior
Reading: Carlin & Louis, Sec 2.1 & 2.2

HOMEWORK 1: Due Mon, Feb 5th in class

1/24.Slides: More on priors
Reading: Carlin & Louis, Sec 2.2 (again), 2.3.1, Optional: discussion on Jeffrey's priors

1/29.Slides: Estimation and decision theory
Reading: Carlin & Louis, Sec B.1

1/31.Slides: The Bias-Variance Tradeoff
Reading: Carlin & Louis, Sec B.2 and 2.3.2

HOMEWORK 2: Due Wed, Feb 14th, in class.

2/5.Slides: Interval Estimation
Reading: Carlin and Louis, 2.3.2.

2/7.Slides: More on interval estimation
Reading: See Sec 4.3.2 of Berger: Statistical Decion Theory and Bayesian Analysis and Sec 5.5.3 of Robert: The Bayesian Choice for additional discussion on credible sets and decision theory (not required)

2/12.Slides: Decisions and hypothesis testing
Reading: Carlin & Louis, Sec B.3 and 2.3.3

2/14.Slides: More on decisions and hypotheses
Reading (optional): Non-local prior densities in Bayesian hypothesis tests, by Johnson and Rossell, 2010

HOMEWORK 3: Due Mon, Feb 26th, in class.

2/19.Slides: Model Comparison
Reading: Bayes Factors, by Kass and Raftery, 1995

2/21.Slides: More on model comparison and assessment
Reading: Carlin & Louis, Sec 2.5 and 4.6.2



3/5.***MIDTERM*** (in class)