Lois was trying to describe point \[A\]'s influence on the \[y\]-intercept in the scatterplot below. A scatterplot has horizontal axis, x, which ranges from negative 2 to 60, in increments of 10; and vertical axis, y, which ranges from 78 to 115, in increments of 10. 1 large point is plotted at (27, 85). 11 individual data points are plotted as follows. (37, 98), (33, 106), (18, 99), (22, 96), (42, 107), (21, 105), (24, 100), (25, 102), (21, 100), (51, 99), and (8, 93). A line rises through (0, 95) and (60, 104). All values estimated. \[\small{0}\] \[\small{10}\] \[\small{20}\] \[\small{30}\] \[\small{40}\] \[\small{50}\] \[\small{90}\] \[\small{100}\] \[\small{110}\] \[x\] \[y\] \[A\] Lois said, "Point \[A\] has a very large negative residual and an \[x\]-value near the mean of the rest of the points, so it's an outlier, but not a high-leverage point. Removing it would lower the entire regression line, so the \[y\]-intercept would decrease." What is the first mistake in Lois's response? Choose 1 answer: Choose 1 answer: