Answer the same questions as in parts (a) and (b) of Problem 1 for each regression of on X, using the data in parts (b), (c), and (d) of Problem 2 in Chapter 5.
In Parts (b), (c), and (d) of Problem 2 in Chapter 5
b. (1) Determine the least-squares estimates of the slope (β1) and intercept (β0) for the straight-line regression of SBP (Y) on QUET (X).
(2) Sketch the estimated regression line on the scatter diagram involving SBP and QUET. Compare this new line with the line you drew in part (a).
(3) Test the null hypothesis of zero slope; be sure to interpret the result.
(4) Based on your test in part (b)(3), would you conclude that blood pressure increases as body size increases?
(5) Find and sketch 95% prediction bands on the appropriate scatter diagram.
(6) Using your answer to part (b)(5), find an approximate 95% prediction interval for an individual with QUET = 3.4 (the sample mean value of QUET). Interpret your answer.
(7) Are any assumptions for straight-line regression clearly not satisfied in this example?
c. Repeat questions (1) through (4) in part (b) for the regression of QUET on AGE.
d. Repeat questions (1) through (4) in part (b) for the regression of SBP on AGE.
The following results will be helpful in reducing computation time:

In Problem 1
a. Determine the ANOVA tables for the following regressions: (1) dry weight (Y) on age (X) and (2) log10 dry weight (Z) on age (X). The following results will be helpful in reducing computation time:
S2Y|X = 0.23218SSY = 8.16811S2Z|X = 0.0007838SSZ = 4.2276839
b. Use the tables in part (a) to perform the F test for the significance of each straight-line regression. Interpret your results.

SBP (Y) regressed on QUET (X): Sri,-96.26743 QUET (Y) regressed on AGE (X): Sn,-0.09079 SBP (Y) regressed on AGE (X): x 85.47795 SSY 6,425.96875 SSY = 7.65968 SSY 6.425.96875