The data below represent commute times (in minutes) and scores on a well-being survey Complete parts (a) through (d) below Commute Time (minutes), $x$ Well-Being Index Score, y \[ \begin{array}{cccccccc} 5 & 15 & 30 & 40 & 60 & 84 & 105 \\ 69.0 & 67.8 & 66.3 & 65.6 & 64.1 & 62.9 & 60.6 \end{array} \] Points: 0 of 1

Step 1 ：The data given represents commute times (in minutes) and scores on a well-being survey. We are asked to find the correlation between these two sets of data.

Step 2 ：The correlation coefficient is a statistical measure that calculates the strength of the relationship between the relative movements of two variables. The values range between -1.0 and 1.0. A correlation of -1.0 shows a perfect negative correlation, while a correlation of 1.0 shows a perfect positive correlation. A correlation of 0.0 shows no relationship between the movement of the two variables.

Step 3 ：We have the following data: commute times (x) = [5, 15, 30, 40, 60, 84, 105] and well-being index scores (y) = [69.0, 67.8, 66.3, 65.6, 64.1, 62.9, 60.6].

Step 4 ：Calculating the correlation between x and y, we get a correlation coefficient of approximately -0.994.

Step 5 ：This indicates a very strong negative correlation between commute time and well-being index score. This means that as commute time increases, the well-being index score tends to decrease, and vice versa.

Step 6 ：Final Answer: The correlation between commute time and well-being index score is approximately \(\boxed{-0.994}\).