Question 6 Assume that each @ is a parameter to be estimated from data, each . Is an independent variable, and Y is the dependent variable. Which of the following models is not considered a linear model? OY = Bot B, X , + Byx, + B,x, X, OY - B. + B, log(x, + Bax, OVY = Bot B, X , + ByX2 O Y = p. + Bix, + x.Question 11 A simple linear regression analysis was conducted for an outcome variable y with one predictor variable X. R2 was computed to be 0.75. Which of the following is the best interpretation of R?? O 0.75 is the correlation between y and the predictor variable X 75% of the variance in y can be explained by the predictor variable O 75% of the time we can accurately predict the outcome Question 12 Which statement is an assumption about least squares regression? Standardized residuals are always less than 3 No heterogeneity in the residual variance All coefficients must be statistically significant The independent variable is normally distributed