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

describing distributions is one of the key skills you’ll need to earn a high score on the ap statistics exam. if you need proof of this, just flip through some past exam questions, which can be found at the collegeboard website. you’ll notice that the first free response question is almost always a question requiring you to look at a graph and describe it.

step-by-step explanation: just trying to get points sorry : (

answer: 1000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000

step-by-step explanation:

x = 12

y = 1

for the points!