Regression Analysis

These are the lecture notes that I used in MTH 34500 - Regression Analysis during the most recent semester in which I taught this course. These resources are html renders of R Notebooks that were created using R studio.

Disclaimer: These notebooks are not intended to be a standalone resource for learning regression analysis. These were created to supplement lecture presentations. Many of the lessons (especially the later ones) would benefit from additional exposition. I hope to eventually develop these into more of a standalone resource.

Lecture Notebooks

• 01 - Intro to Regression
• 02 - Variance and Standard Deviation
• 03 - Least Squares Regression
• 04 - Covariance
• 05 - Hypothetical and Fitted Models
• 06 - Least Squares Regression
• 07 - OLS Regression in R
• 08 - R-Squared
• 09 - Model Assumptions
• 10 - Hypothesis Tests
• 11 - Prediction and Confidence Intervals
• 12 - Example of Prediction and Confidence Intervals
• 13 - Log Transformations (pt1)
• 14 - Log Transformations (pt2)
• 15 - Log Transformations (Diamonds)
• 16 - Intro to Multiple Regression
• 17 - Adjusted r-Squared
• 18 - Example (Galton Data)
• 19 - Qualitative Predictors
• 20 - Best Subset Selection
• 21 - Stepwise Variable Selection
• 22 - Multicolliearity
• 23 - Variance Inflation Factors
• 24 - Lasso and Ridge
• 25 - Logistic Regression
• 26 - Multinomial Logistic Regression