The leverage or h statistic indicates how much influence an observation has on the estimation of the model parameters. Observations with x-values far from the others have larger influence. Move the mouse over each data point to see its leverage value. If all observations fit the regression model well, then omitting one observation should not change the analysis very much. Moving the mouse over the data point not only reveals its leverage value but also shows the regression line with that data point omitted. Examine how omitting certain points affects the regression model. y = 127.47 + (-0.43) x, r-sq = 0.799, 1(5) = -4.46, p = 0.0066 130 120- 110 100 10 25 40 55 70 851. Find the point with the highest leverage value on the graph. When that point is omitted what value does the r-squared assume from its default of 0.799? a. 0.544 b. 0.817 C. 0.864 d. 0.777 -Select- 2. When the highest leverage point is omitted does the model remain significant at a 0.05? a. Yes b. No -Select- V