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Q1:

Descriptive Statistics 

N Minimum Maximum Mean Std. Deviation Median

Price in k€  33 135.0 2000.0 435.955 325.3056 399.00

Floor Area in m² 33 20.5 360.0 74.145 57.8892 65.00

Valid N (listwise) 33

*Important results are highlighted

Model Summaryb 

Model R R Square

 Adjusted R

Square

Std. Error of the

Estimate

1 .974a  .950 .948 74.220

a. Predictors: (Constant), Floor Area in m²

b. Dependent Variable: Price in k€ 

ANOVAa 

Model Sum of Squares df Mean Square F Sig.

1 Regression 3215594.051 1 3215594.051 583.748 .000b 

Residual 170764.571 31 5508.535

Total 3386358.622 32

a. Dependent Variable: Price in k€ 

b. Predictors: (Constant), Floor Area in m²

Coefficients

a

 

Model

Unstandardized Coefficients

Standardized

Coefficients

t Sig.B Std. Error Beta

1 (Constant) 29.939 21.197 1.412 .168

Floor Area in m² 5.476 .227 .974 24.161 .000

a. Dependent Variable: Price in k€ 

Regression Results

Descriptive Statistics for the price and Floor area for Arrondissement XIX 

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Residuals Statisticsa 

Minimum Maximum Mean Std. Deviation N

Predicted Value 142.20 2001.27 435.95 316.997 33

Residual -108.471 246.709 .000 73.051 33

Std. Predicted Value -.927 4.938 .000 1.000 33

Std. Residual -1.461 3.324 .000 .984 33

a. Dependent Variable: Price in k€ 

Scatter plot for Price and Floor Area for Arrondissement XIX

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Q2: Equation of the model

Q3: Analysis of the model

The R² of the model is 0.950, which indicates that 95% of the price can be explained by this

model.

The R of the model is 0.974, which is close to 1, hence we see a strong positive correlation

 between price and floor area.

When checking if R>2/√N 

2/(√ N) of the value is 2/(√33)=0.35.

Therefore, we can reject with a risk of error of 5%, the fact that there is no correlation between

the price and the floor area.

Price=29.939+5.476 X Floor Area

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Q4: Histogram of the variable unstandardized residual

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Q5: Price of an apartment with a floor area = 30 m^2

Expected price of a 30 M² apartment

= 29.939+5.476 X 30

= €194.219 

σ² =5508.535σ = 74.22 

Therefore there is 95% chance that the price is between [194.22-2x74.22, 194.22+2x74.22]

[€ 45.78 , € 342.66]