BIST-620-01 Generalized Linear Model
Fall for 2017-2018

The course will cover statistical methods for analyzing non normally distributed data such as proportion, count, and rate data using generalized linear models. The course will cover topics relating to estimation, inference, deviance, diagnosis using both the frequentist and Bayesian framework. The applications include two-way tables; multi-factor, multivariate-responses, variable selection, repeated measurement experiments.

Credits: 3
Prerequisites: Offered ONLY to BIST PhD Students.
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