13. We've seen how residuals are used to assess the fit of a regression line to the data, but they have another important role. How are residuals used in the definition of the least-squares regression? (2 points) The line that minimizes the squared sum of the residuals is known as the least squares regression line (LSRL). ( Residual = observed point - predicted value ) Since the residual in a LSRL have a mean of zero, their variance is equal to the average of the squares OF the residuals. This is how residuals are used in the least- squares regression definition.Base Hits Runs Home Runs 136 130 94 63 36 25 122 123 91 78 35 25 108 141 95 77 33 24 115 130 89 65 32 24 106 114 88 66 24 32 87 128 63 79 31 24 140 70 116 73 31 23 101 117 70 63 29 23 123 74 86 57 28 22 144 85 28 109 71 28 132 62 27 93 74 27 122 80 27 with the regression line (the equation choo 143 74 26 133 86 25 130 66 here. (The sketch does not need to 24 101 58 23 inear? Why or why not? (1:5 points 104 50 23 102 73 23 data seems to be liveher 135 77 23 157 74 22 it Follows the recreation 87 50 22 101 50 21 160 99 21 134 91 47 109 86 47 131 108 36 136 86 31 133 91 30 149 78 29 123 96 29 89 71 29 136 74 28 132 62 27 137 77 27 125 70 27 103 68 26 118 83 26 89 60 26 128 57 26 Data is continued in the next column