1. Chapter 12 Inference on the Least-squares Regression Line; ANOVA
12.1
Inference about the Least-squares Regression Line

6. The standard error of the estimate, se , is found using the formula

7. EXAMPLE Computing the Standard Error
Determine the standard error of the drilling data. The data is given on the next slide.

9. EXAMPLE Verifying the Normality of the Residuals
Verify that the residuals for the drilling data are normal.

12. Step 1. A claim is made regarding the linear relation between a response variable, y, and a predictor variable, x. The claim is used to determine the null and alternative hypothesis. The hypothesis can be structured in one of three ways.

17. Step 3. Compute the test statistic
which follows Student’s t-distribution with n – 2 degrees of freedom.

18. Step 4: Compare the critical value with the test statistic:

19. EXAMPLE Testing for a Linear Relation

20. Confidence Intervals for the Slope of the Regression Line

21. EXAMPLE Confidence Interval for Slope
Construct a 95% confidence interval for the slope of the least-squares regression line for the drilling data.