STA140 Statistical Decision Analysis
Section 01
Fall 2009

Instructor:
I. H. Dinwoodie, 219 Old Chemistry Building
Office Hours:
Tu: 4:05-5:00
We: 10:00-11:00
Th: 4:05-5:00
Lecture:
Tu, Th, 2:50-4:05, Soc Sci 228
Summary:
This course will cover topics in three areas of decision sciences:
I) Individual decisions under ignorance and uncertainty: minimax strategies, probabilities, expected utility. Reference: Resnik, Chapters 1-4.
II) Statistical Decision Theory: Loss functions, risk, expected utility and optimization, minimax (maximin) solutions, admissible solutions and Bayes solutions, computation of Bayes solutions. Reference: Moses and Chernoff, Chapters 5,6.
III) Two-person games: minimax (maximin) strategies, saddle point solutions and equilibria, mixed strategies. Reference: Resnik, Chapter 5.
Applications will be made to betting, economics, and finance. Computational exercises in statistics and optimization will be done in Microsoft Excel (with free add-ins for decision trees) and R. Students will be required to do computational exercises on Windows computers.
Required Texts:
M. D. Resnik, Choices, An Introduction to Decision Theory, University of Minnesota Press, ISBN 978-0816614400.
H. Chernoff, and L. Moses, Elementary Decision Theory, Dover, New York, ISBN 978-0486652184. (This book is not in the bookstore and is currently out-of-print, but used copies should be available on the web. There is a copy on overnight reserve in Perkins for consultation.)
Other references:
Final Project Due Date:
Saturday December 12, 7 P.M. at the regular classroom (schedule).
Midterm Exams:
Thursday October 8 (covers Chapters 1-3 of Resnik, homework and labs)
Tuesday November 17
Grading:
The final grade will be based on the final project (20%), two midterm exams (20% each), and homework (40%). Homework will be collected and graded each week, and three of them will be computer labs (lab 1, lab 2, lab 3).