A real estate agent in Athens used regression analysis toinvestigate the relationship between apartment sales prices and thevarious characteristics of apartments and buildings. The variablescollected from a random sample of 25 compartments are asfollows:
Sale price: The sale price of the apartment (in €)
Apartments: Number of apartments in the building
Age: Age of the building (in years)
Size: Apartment size (area in square meters)
Parking spaces: Number of car parking spaces in the building
Excellent building condition (Pseudo-variable): 1 if the conditionof the building is
excellent, 0 different
Good building condition (Pseudo-variable): 1 if the condition ofthe building is
good, 0 different

We have the following results of regression analysis with the OLSmethod:

Coefficientsa
Model	Unstandardized Coefficients	Standardized Coefficients	t	Sig.
B	Std. Error	Beta
1	(Constant)	98308,606	22888,689		4,295	,000
Apartments	5776,999	1215,251	,344	4,754	,000
Age	-905,594	269,262	-,111	-3,363	,003
Size	1237,643	142,945	,586	8,658	,000
Parking space	2966,996	1313,465	,096	2,259	,037
Excellent	52337,908	19957,138	,108	2,623	,017
Good	5543,922	16714,509	,013	,332	,744
a. Dependent Variable: Sale price

Questions:
1. State the estimated regression equation.

2. Comment on the importance of the regression rates.

3. Give the interpretation of the regression coefficients.