In this chapter, you will learn how to:
- Write and interpret a simple linear regression equation;
- Fit and visualize a simple linear regression model;
- Interpret the estimated regression coefficients for a model with a continuous predictor;
- Interpret the estimated regression coefficients for a model with a categorical predictor;
- Test the significance of a single regression coefficient;
- Use a multiple degree of freedom test to test the significance of multiple coefficients simultaneously;
- Compute predictions from the model;
- Compute confidence intervals for the regression coefficients;
- Compute and visualize confidence intervals for the mean outcome;
- Compute and visualize confidence intervals for individual observations; and
- Fit and visualize a curve using a polynomial function.
Some of the R programming code used in this chapter uses elements of the
tidyverse library (Hadley Wickham 2023), in particular the pipe operator
%>% and functions such as
mutate(). Load this library before proceeding.