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Midterm prep: categorical data, GLMs
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Module 3
Introduction to Generalized Linear Models (GLMs)
1
Beyond Linearity: When and Why GLMs Outperform OLS
Explain the limitations of linear regression that motivate the use of GLMs.
2
Understanding the Three Components of GLMs
Identify the three components of a GLM: random component, systematic component (linear predictor), and link function.
3
Link Functions and Canonical Links
Define the purpose of a link function and identify the canonical link for common distributions (Normal, Poisson, Binomial).
4
Choosing Distributions and Link Functions for GLMs
Given a description of a response variable, select an appropriate distribution and link function for a GLM.
Previous module
Contingency Table Analysis: Chi-Square and Fisher's Tests
Next module
The Exponential Family of Distributions