First, the reason for this question is that I believe that nutrition plays a part in a student's ability to focus and excel in school. If a student is eligible for subsidized lunch, likely they are not receiving healthy nutritious meals for breakfast and dinner. And a lower average family income is probably related to students' ability to receive subsidized lunches. However, other factors besides for average income contribute to eligibility; for that reason, test scores may be affected differently when compared to meal_pct and/or avginc.

The formula for this:
average test score = B0 + B1meal_pct + B2avginc + B3(meal_pct*avginc) + u

The formula for creating a variable representing the B3 component (interaction term):
gen stud_fin_state = meal_pct*avginc

A regression on JUST scores and meal_pct:
reg testscrmeal_pct, r

Finally, the regression which will test for the interactive relationship:
reg testscrmeal_pctavgincstud_fin_state, r

Based on what the two regressions show us, how can you interpret the coefficient on meal_pct? And the slight change between models one and two?

Is there a significant interactive relationship between the variables?

How could you visually (graphically) demonstrate?

Make sense out of that question and answer accordingly

Attachment:- Question.rar