The following table, based on data from the credit reporting company Experian, presents the average number of late payments and the average credit score for residents of selected U.S. cities in 2012.

a. Compute the correlation between the number of late payments and the credit score.

b. Compute the least-squares line for predicting average credit score \((y)\) from average number of late payments \((x)\).

c. Construct a residual plot. Are the residuals corresponding to \(x \geq 0.5\) more spread out than those corresponding to \(x

d. Compute the least-squares line using only those points with \(x

e. Compute the least-squares line using only those points with \(x \geq 0.5\).

f. Compute the coefficient of determination using only those points with \(xg. Compute the coefficient of determination using only those points with \(x \geq 0.5\).
h. In which situation is the average number of late payments more strongly related to average credit score, when the average number of late payments is less than 0.5 or when it is greater than or equal to 0.5 ?

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Late Payments 0.50 0.50 0.45 0.52 0.65 0.26 0.30 0.58 0.67 0.41 0.58 0.46 0.42 0.50 Credit Score 729 727 758 731 755 778 772 729 739 761 717 752 767 742 Late Payments 0.24 0.34 0.25 0.53 0.51 0.73 0.65 0.68 0.40 0.53 0.57 0.45 0.25 0.52 Credit Score 777 776 771 724 740 702 729 714 739 746 711 766 787 731 Late Payments 0.33 0.60 0.33 0.39 0.51 0.33 0.37 0.33 0.39 0.33 0.21 0.41 0.43 Credit Score 762 733 769 760 737 772 767 762 761 776 784 767 752