The data below represent commute times (in minutes) and scores on a well-being survey. Complete parts (a) through (d) below. Commute Time (minutes), x 20 25 40 60 72 105 Well-Being Index Score, y 69.0 67.1 66.3 64.9 63.0 62.6 58.7 (a) Find the least-squares regression line treating the commute time, x, as the explanatory variable and the index score, y, as the response variable. y =- 0.098 x + (69.099) (Round to three decimal places as needed.) (b) Interpret the slope and y-intercept, if appropriate. First interpret the slope. Select the correct choice below and, if necessary, fill in the answer box to complete your choice. O A. For every unit increase in commute time, the index score falls by , on average. (Round to three decimal places as needed.) O B. For an index score of zero, the commute time is predicted to be minutes. (Round to three decimal places as needed.) O C. For every unit increase in index score, the commute time falls by , on average. (Round to three decimal places as needed.) O D. For a commute time of zero minutes, the index score is predicted to be (Round to three decimal places as needed.) 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 your choice. O A. For an index score of zero, the commute time is predicted to be minutes. (Round to three decimal places as needed.) O B. For a commute time of zero minutes, the index score is predicted to be (Round to three decimal places as needed.) O C. For every unit increase in commute time, the index score falls by . on average. (Round to three decimal places as needed.) O D. For every unit increase in index score, the commute time falls by , on average. (Round to three decimal places as needed.) O E. It is not appropriate to interpret the y-intercept because a commute time of zero minutes does not make sense and the value of zero minutes is much smaller than those observed in the data set