Chapter 6: Simple Linear Regression

This set of labs introduces the simple linear regression model: fitting a least squares model, interpreting a line of best fit, and making inferences about a population.
Lab Notes

1. Introduction to Least Squares Regression

Introduces the idea of using a straight line to summarize data that exhibit an approximately linear relationship and the mechanics of fitting and interpreting a line of best fitFormally introduces , in addition to presenting the statistical model for least squares regression and discussesing the residual plots used to assess the assumptions for linear regression.

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2. Understanding R2

Explores the idea behind the quantity R2 by sampling observations according to a population regression model with known parameters

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3. Categorical Predictors with Two Levels and Inference in Regression

Discusses the use of binary categorical predictor variables and the extension of statistical inference to a regression context.

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R (Base), Useful Links

The statistical software R is a widely used and stable software that is free. RStudio is a user-friendly interface for R.