The data below represent the number of days absent, x, and the final grade, y, for a sample of college students at a large university. Complete parts (a) through (e) below. No. of absences, x 1 2 3 4 5 6 7 8 Final grade, y 88.9 85.9 82 9 80.5 774 730 63.6 67 8 649 61.9 (a) Find the least-squares regression line treating the number of absences, x, as the explanatory variable and the final grade, y, as the response variable. y = x + (ID (Round to three decimal places as needed. ) (b) Interpret the slope and y-intercept, if appropriate. Interpret the slope. Select the correct choice below and, if necessary, fill in the answer box to complete your choice (Round to three decimal places as needed.) O. A. For every unit change in the final grade, the number of days absent falls by days, on average OB. For every day absent, the final grade falls by on average O C. For zero days absent, the final score is predicted to be O D. For a final score of zero, the number of days absent is predicted to be days O E. It is not appropriate to interpret the slope. Interpret the y-intercept. Select the correct choice below and, if necessary, fill in the answer box to complete yourFinal grade, y 889 85 9 829 80 5 77 4 73.0 636 678 649 619 Interpret the y-intercept. Select the correct choice below and, if necessary, fill in the answer box to complete your choice: (Round to three decimal places as needed.) O A. For zero days absent, the final score is predicted to be O B. For every day absent, the final grade falls by .on average. O C. For a final score of zero, the number of days absent is predicted to be day's O D. For every unit change in the final grade, the number of days absent falls by days, on average O E. It is not appropriate to interpret the y-intercept (c) Predict the final grade for a student who misses five class periods and compute the residual Is the observed final grade above or below average for this number of absences? The predicted final grade is .This observation has a residual of .which indicates that the final grade is average (Round to one decimal place as needed ) Idi Draw the least-squares morassion line on the shafter diagram of the data Change the correct graph below NextO A. O B. OC. OD. 100 Ay 100 100 100- 50 50 50 (e) Would it be reasonable to use the least-squares regression line to predict the final grade for a student who has missed 15 class periods? Why or why not? O A. No-15 missed class periods is outside the scope of the model. O B. No-15 missed class periods is not possible and outside the scope of the model, O C. No-15 missed class periods is not possible. O D. Yes-15 missed class periods is possible and within the scope of the model O E. More information regarding the student is necessary to be able to make a decision. Next