Univariate and multivariate statistical techniques for continuous and dichotomous outcomes. Focus is on multiple linear and logistic regression models. Additional topics will include adjusting for missing data, measurement error, and hierarchical (random effects) models. All material will be taught from both Bayesian and frequentist viewpoints. R and WinBUGS software will be used throughout the course.

January 9 to April 18, 2012. Mondays and Wednesdays, 9:00 AM to 11:00 AM. Room 25, Purvis Hall, 1020 Pine Avenue West.

Assignments = 5 * 2% (each) = 10%, Midterm Exam = 25%, Project = 15%, Final Exam = 50%.

Assignment 1: due January 25th, 2012
Assignment 2: due February 13th, 2012
Assignment 3: due March 12th, 2012
Assignment 4: due March 26th, 2012
Assignment 5: due April 20th, 2012

Michael H. Kutner, John Neter, Christopher J. Nachtsheim, William Li. Applied Linear Statistical Models, 5th Edition, McGraw-Hill, 2005.
David W. Hosmer and Stanley Lemeshow, Applied Logistic Regression, 2nd Edition Wiley, 2000.
George G. Woodworth. Biostatistics: A Bayesian Introduction. Wiley, New York, 2004.
Andrew Gelman, John Carlin, Hal Stern and Donald. Rubin, Bayesian Data Analysis, 2nd Edition, Chapman and Hall, 2003.

Previous courses in differential and integral calculus, and EPIB 607 or equivalent.