To elaborate: Suppose that you have a single quantitative dependent variable (y) and two quantitative independent variables (x1 and 2). If you observe a high degree of linear correlation between 1 and 2. does this imply that the relationship between 1 and y depends on x2? True False Question 10 4 pts Suppose that we have a single quantitative dependent variable (y), a quantitative independent variable (x1), and a qualitative independent variable (x2). Suppose that you have completed the "best" model process and have plotted your "best" model in a scatterplot with your actual data (x1 by y with X2 used as a plotting symbol). If you observe that points further up the line(s) lie., further along the x1 axis) are drastically more spread out (from the line) than points lower on the line(s), then you likely have an issue with which of the following linear regression assumptions? Choose only one option. Independence of errors Multicollinearity Normality of errors Constant variance Mean error equals 0