The residuals track the diagonal reference line and remain inside the adjacent bands. These residuals are nearly normal. Fortunately, inferences about β0 and β1 work well even if the data are not normally distributed. Confidence intervals for the slope and intercept are reliable even if the errors are not normally distributed. As when finding confidence intervals for μ, this claim relies on the Central Limit Theorem.
If the residuals are not normally distributed, check the sample size condition for the residuals (as in Chapter 14). The sample size should be larger than 10 times the absolute value of the kurtosis K4 of the residuals.
Modeling ...
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month, and much more.
Fortunately, inferences about β0 and β1 work well even if the data are not normally distributed. Confidence intervals for the slope and intercept are reliable even if the errors are not normally distributed. As when finding confidence intervals for μ, this claim relies on the Central Limit Theorem.