My notes (unofficial) from Leo Kahane's book Introduction to Regression, 1st Edition.

The code in the book presents example for Excel and SPSS.

This page shows the code in R.

Author's Website
On Amazon

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Chapters

• Ch. 1 - Introduction to Regressions
• Ch. 2 - Basic Examples and Assumptions
• Ch. 3 - Model Performance and Evaluation
• Ch. 4 - Multiple Regression Analysis
• Ch. 5 - Nonlinear, Dummy, Interaction and Time Variables

Motivation

While competing in this Kaggle competition, the baseline model used a linear mixed effects regression model (lmer). In my attempts to understand the lmer model, I had to go back to basics and refresh myself on simple linear regressions.

Clearly I still have to learn as I finished in 56th place out of 257 competitors.

Further Resources

[Jake Hofman's Data-Driven Modeling Class at Columbia] (http://jakehofman.com/ddm/2012/03/lecture-05/?utm_source=rss&utm_medium=rss&utm_campaign=lecture-05)

Andrew Ng's Introduction to Machine Learning Class at Stanford

lme4 class for linear mixed effects regressions in R

Getting the Code, Notes, and Data

git clone github.com/idrisr/Regression.git