The variable smokes is a binary variable equal to one if a person smokes, and zero otherwise. An estimated linear probability model for smokes is given as follow:

The variable white equals to one if the respondent is white, and zero otherwise; the other independent variables are cigpric (per-pack rice of cigarettes in cents), income (annual income), educ (years of schooling), age (measured in years), restaurn (a binary indicator equal to one if the person resides in a state with restaurant smoking restrictions). Both the (usual) and the [heteroskedasticity-robust] standard errors are reported.

a) Are there any important differences between the two sets of standard errors?

b) Holding other factors fixed, if education increases by four years, what happens to the estimated probability of smoking?

c) At what point does another year of age reduce the probability of smoking?

d) Interpret the coefficient on the binary variable restaurn.

e) Person #206 in the data set has the following characteristics: cigpric = 67.44, income = 6500, educ = 16, age = 77, restaurn = 0, white = 0, smoke=0. Compute the predicted probability of smoking for this person and comment on the result.