Q. 1. Find the sample correlation coefficient between X and Y.
2. How would you decide if a simple linear regression model is appropriate for the relationship between X and Y?
3. If a simple linear regression model is indeed appropriate for the relationship, find the estimated regression line. And interpret this line.
4. Find the predicted compensation with the productivity of 100. What is the residual for the observation of the base year, 1992?
5. Is there strong evidence that the compensation is linearly related to productivity? Justify your answer.
6. Find a 95% confidence interval for the slope parameter.
7. Is there strong evidence that is greater than 0.65? Justify your answer using the level of significance = 0.05.
8. Find an estimate for the variance of the error in the simple linear regression model.
9. Find the 90% confidence interval for the mean compensation when the productivity is 85 and interpret the C.I.
10. Find the 90% confidence interval for the compensation of a year when the productivity is 85and interpret the C.I.
11. Check the normality assumption.