What are Generalized Linear Models, and what do they generalize?

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“GLM in R” Course Outline:
Administration
* Administration
Up to Scratch
* Notebook – Introduction
* Notebook – Linear Models
* Notebook – Intro to R
Intro to GLM’s
* Linear Models vs. Generalized Linear Models
* Least Squares vs. Maximum Likelihood
* Saturated vs. Constrained Model
* Link Functions
Exponential Family
* Definition and Examples
* More Examples
* Notebook – Exponential Family
* Mean and Variance
* Notebook – Mean-Variance Relationship
Deviance
* Deviance
* Notebook – Deviance
Likelihood Analysis
* Likelihood Analysis
* Numerical Solution
* Notebook – GLM’s in R
* Notebook – Fitting the GLM
* Inference
Code Examples:
* Notebook – Binary/Binomial Regression
* Notebook – Poisson & Negative Binomial Regression
* Notebook – Gamma & Inverse Gaussian Regression
Advanced Topics:
* Quasi-Likelihood
* Generalized Estimating Equations (GEE)
* Mixed Models (GLMM)

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* Extra material (notebooks)
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GLM (restricted) playlist: https://bit.ly/2ZMSv4U

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