May 16, 2022  
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2021-2022 Catalog

DS 407 - Advanced Statistics/Statistical Modeling

Generalized linear models (GLMs) are valuable regression techniques that can be used to model most types of data. This course introduces you to the theory and application of generalized linear models to analyze data. Following a review of linear regression, you will explore a central element of GLMs—maximum likelihood estimation. You will find out how to interpret the results from GLMs and how to apply them to a variety of data types including proportion (binomial distribution), count (Poisson and negative binomial distributions), continuous (gamma and inverse Gaussian distributions), and data Tweedie distributions. By the end of this course, you will be able to use GLMs to model a variety of data types and perform analysis using generalized linear models in R.

Prerequisites & Notes
Student has completed or is in process of completing any of the following course(s): DA 309 - Essentials of Biostatistics

Credits: 3