School of Public Health

 

Department of Biostatistics


PubH 8432 Probability Models- Fall 2009


Course Description

The course will focus on the constructio and statistical analysis of probability models for real data. The course will provide a non-measure theoretic introduction to Markov chains, Discrete and Continuous Markov processesses, Hidden Markov Models, Markov random fields etc. All these models will be illustrated with examples. The application of these stochastic models in wide variety of fields such as Genetics, Epidemiology, Social Science will be discussed. Markov Chain Monte Carlo methds will be discussed briefly.

This is a 3 credit course. Prequisites are Stat 5101-2 or equivalent; PubH8420 and PubH8421; or instructor's consent. Some experience with Splus or R is useful; Real Analysis/Advanced Calculus at the level of Math5615 is needed.

Time: Tuesday and Thursday 9:45-11:00AM
InstructorDr.Saonli Basu, Mayo A 454-3. Ph: (612) 624-2135. Email: saonliATbiostat.umn.edu
Office Hours:Monday 3:00-5:00 PM
Location: Mayo 1250
TA Rajarshi Guha Niyogi
Office Hours:TBA
For whom intended: This course is designed for biostatistics/statistics graduate students.
Prerequisites: requisites are Stat 5101-2 or equivalent; PubH8420 and PubH8421; or instructor's consent. Some experience with Splus or R is useful; Real Analysis/Advanced Calculus at the level of Math5615 is needed.
Evaluations: Course evaluation will be based on homework assignments (40%), Midterm (30%) and a final project (30%).
Course web site: PubH 8432

Textbook: The textbook for this course:

The material will also be drawn from the following texts: