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 first floor square footage*Beach. Term Estimate Std. Error
Intercept -93.4 214.5
Beach 782.5 31.45
firstfloorsquarefootage 0.412 0.120
firstfloorsquarefootage*Beach 0.004 0.012
How would you interpret the slope coefficient for first floor square footage?
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.
d. The slope of the relationship between firstfloorsquarefootage and price is moresteep for homes near the beach than elsewhere in Tampa.
Step-by-step explanation:
In this regression model, we have a positive slope. This positive slope is indicative of an increase. So to interpret this slope, we would say that the slope of the relationship that exists between the two variables (price and firstfloorsquarefootage) is steeper for the homes that are closer to the beach compared to the ones that are elsewhere. Therefore option D is our answer.
