Seventy homes that were for sale in Tampa, Florida in Spring of 2019 were randomly selected. A regression model to predict house price was run based on first floor square footage and the indicator variable for Beach (1 if the house was within 1 mile of the beach, 0 if not). There was also an interaction term for firstfloorsquarefootageBeach.
Term Estimate Std. Error
Intercept -93.4 214.5
Beach 782.5 31.45
firstfloorsquarefootage 0.412 0.120
firstfloorsquarefootageBeach 0.004 0.012
How would you interpret the slope coefficient for firstfloorsquarefootage*Beach?
A. Homes near the Beach are less expensive than elsewhere for a given size.
B. The slope of the relationship between firstfloorsquarefootage and price is lesssteep for homes near the beach than elsewhere in Tampa
C. Homes near the Beach are more expensive than elsewhere for a given size.
D. The slope of the relationship between firstfloorsquarefootage and price is moresteep for homes near the beach than elsewhere in Tampa

We can see from the output that was run in this regression that this variable has a positive coefficient. So the result is going to be interpreted to show an increase. Therefore d is the answer as it shows that these homes which are closer to the beach are steeper compared to those that are in other areas of tampa. It's necessary to always look out for the signs of the coefficient when interpreting a regression result