The primary distinction between a linear probability model and linear regression model is:
A. the standard errors of a linear probability model will be larger.
B. you can't interpret the coefficients in a linear probability model.
C. a linear probability model never suffers from heteroscedasticity.
D. the outcome is dichotomous in a linear probability model.
Answer: D
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