Module 4: Linear Regression
In this module, we will take a deep dive on linear regression.
I have split this into four parts: introduction, inference, diagnostics, and transformations.
Lecture Videos: Introductory
Lecture Notes
Lecture notes displayed in the lectures can always be found at the lecture notes website.
Simple Linear Regression
An Example of Linear Regression
Ordinary Least Squares
Interpreting Regression Models
Predictions from the Model
Inference and Hypothesis Tests from an OLS Model
Coefficients and their Confidence Intervals
Lecture Videos: Inference
Lecture Notes
Lecture notes displayed in the lectures can always be found at the lecture notes website.
Sums of Squares
Review of Linear Model Output
The F-test
ANOVA in R
Model Uncertainty
Standard Errors and Predictions
Confidence and Prediction Intervals
Confidence and Prediction Intervals in R
Lecture Videos: Diagnostics
Lecture Notes
Lecture notes displayed in the lectures can always be found at the lecture notes website.
Assumptions and Diagnostics
Checking Residuals
Residual Plots
Outliers
Alternative Views of Residual Plots
Removing Outliers
Lecture Videos: Transformations
Lecture Notes
Lecture notes displayed in the lectures can always be found at the lecture notes website.
Introduction to Transformations
Most Common Transformations
Cars Data and Weight
Removing Outliers with Transformed Data
Interpreting the Transformed Model โฆ Or Not
Transformed Predictions (numbers in disguise๐)
๐ Recommended Reading & Other Content
Crash Course
A Very Normal description of linear regression
Pelleriti Lecture
A great introductory lecture on linear regression by another professor