In this first Chapter of part II we will begin with fitting simple regression using the function lm(). We'll also look at satisying regression assumptions, making predictions from models, and testing hypotheses about regression parameters.
Upon completion of this lesson, you should be able to:
- Fit simple linear regression models in R using the function lm()
- Use diagnostic plots to check model residuals for violations of assumptions
- Use predict() to calculate predicted values, confidence intervals, and prediction intervals
- Test hypotheses about regression parameters
The R code file and data files for this lesson can be found on the Essential R - Notes on learning R page.