andrew w. moore | A primer for linear regression
In 2021, I wrote a series of blog posts that cover the basics of linear regression. My partner was in the midst of completing her Masters program, and I was providing some help to get her started in a course using quantitative methods. The goal of this 3-part series is to provide the reader with a basic understanding of what linear regression is, how to fit linear regressions using R, and check some basic assessments of statistical fit. I was inspired by the approach that Gelman & Hill use in their textbook (among other resources I mention), but wanted to provide a distilled version that I could pass on to a colleague that's needing an overview. I've moved the series to this part of the site because each section is lengthy, and the content is a bit different from my usual blog posts.
Part 1 | Ordinary Least Squares |
Part 2 | Fitting a model using R |
Part 3 | Multiple regression and model comparison |