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


Related Solutions

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...
A real estate agent wants to study the relationship between the size of an apartment and...
A real estate agent wants to study the relationship between the size of an apartment and its monthly rent price. The table below presents the size in square feet and the monthly rent in dollars, for a sample of apartments in a suburban neighborhood. Rent ($) 720 595 915 760 1000 790 880 845 650 748 685 755 815 745 715 885 Size (Square Feet) 1000 900 1200 810 1210 860 1135 960 800 960 650 970 1000 1000 1000...
The commercial division of a real estate firm is conducting a regression analysis of the relationship...
The commercial division of a real estate firm is conducting a regression analysis of the relationship between x, annual gross rents (in thousands of dollars), and y, selling price (in thousands of dollars) for apartment buildings. Data were collected on several properties recently sold and the following computer output was obtained. The regression equation is Y = 20.0 + 7.25 X Predictor Coef SE Coef T Constant 20.000 3.2213 6.21 X   7.250 1.3624 5.29 Analysis of Variance SOURCE DF SS...
The commercial division of a real estate firm is conducting a regression analysis of the relationship...
The commercial division of a real estate firm is conducting a regression analysis of the relationship between x, annual gross rents (in thousands of dollars), and y, selling price (in thousands of dollars) for apartment buildings. Data were collected on several properties recently sold and the following computer output was obtained. Analysis of Variance SOURCE DF Adj SS Regression 1 41587.3 Error 7 Total 8 51984.1 Predictor Coef SE Coef T-Value Constant 20.000 3.2213 6.21 X 7.210 1.3626 5.29 Regression...
The commercial division of a real estate firm is conducting a regression analysis of the relationship...
The commercial division of a real estate firm is conducting a regression analysis of the relationship between x, annual gross rents (in thousands of dollars), and y, selling price (in thousands of dollars) for apartment buildings. Data were collected on several properties recently sold and the following computer output was obtained. Analysis of Variance SOURCE DF Adj SS Regression 1 41587.3 Error 7 Total 8 51984.1 Predictor Coef SE Coef T-Value Constant 20.000 3.2213 6.21 X 7.210 1.3626 5.29 Regression...
The commercial division of a real estate firm is conducting a regression analysis of the relationship...
The commercial division of a real estate firm is conducting a regression analysis of the relationship between , annual gross rents (in thousands of dollars), and , selling price (in thousands of dollars) for apartment buildings. Data were collected on several properties recently sold and the following computer output was obtained. The regression equation is Y= 20.0 +7.25 X Predictor Coef SE Coef T Constant 20.000 3.2213 6.21 X 7.250 1.3625 5.29 Analysis of Variance SOURCE DF SS Regression 1...
The commercial division of a real estate firm is conducting a regression analysis of the relationship...
The commercial division of a real estate firm is conducting a regression analysis of the relationship between x, annual gross rents (in thousands of dollars), and y, selling price (in thousands of dollars) for apartment buildings. Data were collected on several properties recently sold and the following computer output was obtained. Analysis of Variance SOURCE DF Regression 1 Error 7 Total 8 Predictor Coef Constant 20.000 X Adj SS 41587.3 51984.1 SE Coef T-value 3.2213 6.21 1.3626 5.29 (a) How...
A real estate agent (Sue Bays Realty) wants tot study the relationship between the size of...
A real estate agent (Sue Bays Realty) wants tot study the relationship between the size of a house and its selling price. The table below presents the size in square feet and the selling price in thousands of dollars, for a sample of houses in a suburban neighborhood. Size (Square Feet) Selling Price ($1000s) 2521 400 2555 426 2735 428 2846 435 3028 469 3049 475 3198 488 3198 455 Calculate the correlation between these two variables. Calculate the Predicted...
The Sales Manager at City Real Estate Company is interested in describing the relationship between condo...
The Sales Manager at City Real Estate Company is interested in describing the relationship between condo sales prices and the number of weeks the condo is on the market before its sells. He has collected a random sample of 17 low end condos that have sold within the past three months. These data are as follows: Weeks on the Market Selling Price 23 $                76,500.00 48 $             102,000.00 9 $                53,000.00 26 $                84,200.00 20 $                73,000.00 40 $             125,000.00...
You are the real estate sales agent for the Martins who are selling a home to...
You are the real estate sales agent for the Martins who are selling a home to the Howells. The Martins signed a purchase agreement with the following personal property stipulated: The tools in the garage, and the refrigerator, besides the paintings in the living room, will remain the property of the seller. The signed contract has just been received by the Martins and they call you as their sales agent to add the bookcase in the master bedroom as another...
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT