The advantage of using the probit model versus the linear probability model for estimating regressions for binary dependent variables is: A. probit model yields more precise estimates (i. e. lower standard errors of the estimated coefficients) B. regression coefficients in the probit model are easier to interpret C. probit model yields predicted probabilities that lie between 0 and 1 D. all of the above