#Exercise 5.d:
# Load the data into R with the command:
pef.data = data.frame(pef = c(494,395,516,434,476,413,442,433),
minipef = c(512,430,520,428,500,364,380,445))
# Fit a linear regression model with "minipef" as the outcome and "pef" as the predictor.
# Use the formulas from the slides to generate the same estimates you get in the summary of the model. That is:
- The residual standard error
- Multiple R-squared
- Adjusted R-squared
- Fstatistic
- p-value