Question

In: Statistics and Probability

A real estate agent in Athens used regression analysis to investigate the relationship between apartment sales...

A real estate agent in Athens used regression analysis to investigate the relationship between apartment sales prices and the various characteristics of apartments and buildings. The variables collected from a random sample of 25 compartments are as follows:
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 condition of the building is
excellent, 0 different
Good building condition (Pseudo-variable): 1 if the condition of the building is
good, 0 different


We have the following results of regression analysis with the OLS method:

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.

Solutions

Expert Solution

The estimated regression equation, as sale is the depedent variable would be:

1. Sale = 22888689 + 1215251*Apartment + 269262*Age +142945*Size + 1313465*Parking Space + 19957138*Excellent + 16714509*Good

2. From the given output of the regression analysis, we found the P-Value (Sig.) of Apartment, Age, Size, Parking Space and Excellent as 0.000, 0.003, 0.000, 0.037, 0.017 respectively which is less than the level of significance 0.05, therefore we reject the null hypothesis and conclude that there is statistically significant impact on sale of the explanatory variables Apartment, Age, Size, Parking Space and Excellent.

3. As the one unit change in explanatory variables Apartment, Age, Size, Parking Space, Excellent and Good then there must be the sale 62501259 Euro.

Sale = 22888689 + 1215251*1 + 269262*1 +142945*1 + 1313465*1 + 19957138*1 + 16714509*1

Sale = 22888689 + 1215251 + 269262 +142945 + 1313465 + 19957138 + 16714509


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