Regression Diagnostics (1/2) - Linear Models - Residuals, QQ-plot, Outliers

In this video we will look at how we can diagnose our linear regression fit using residuals, QQ-plots and Cook's distance.
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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)
* Regular vs. Mixed Models
Multinomial Regression
* Intro
* Nominal Data - Baseline Category
* Ordinal Data - Cumulative Link
Diagnostics
* Linear Regression Diagnostics
* Generalized Linear Model Diagnostics
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[@ML_n00b]

very useful video for practitioners