1.) Suppose you have four classifications: freshmen (f), sophomore (so), junior (j), and senior (se). You construct a dummy variable, one for each classification that takes on the value of (1) should that classification be true for that observation and 0 otherwise.

Further assume that you estimate the following model:

E[GPA]= .5*ACT+.1*So+.2*J+.1*Se

What is the omitted category?

Enter 1 for Freshmen, 2 for Sophomores, 3 for Juniors, 4 for Seniors.

2.) Suppose you have four classifications: freshmen (f), sophomore (so), junior (j), and senior (se). You construct a dummy variable, one for each classification that takes on the value of (1) should that classification be true for that observation and 0 otherwise.

Further assume that you estimate the following model:

E[GPA]= .5*ACT+1*So+0.43*J+{c}*Se

How much higher/lower is a Junior's GPA, after controlling for ACT, than for the omitted category?

3.) Suppose you have two classifications: female and male. The dummy variable, f, takes the value of 1 if the individual is a female, 0 if male. Given the followingmodel:

E[GPA]= 0+0.07*ACT+0*f+0*f*ACT

What is the marginal effect of a unit increase in ACT on E[GPA] for females?

4.) Suppose you have two classifications: female and male. The dummy variable, f, takes the value of 1 if the individual is a female, 0 if male. Given the followingmodel:

E[GPA]= 0+0.04*ACT+{a)*f+0*f*ACT

What is the marginal effect of a unit increase in ACT on E[GPA] for males?