3. United Park City Properties real estate investment firm took a random sample of five condominium units that recently sold in the city. The sales prices Y (in thousands of dollars) and the areas X (in hundreds of square feet) for each unit are as follows
Y= Sales Price ( * $1000) |
36 |
80 |
44 |
55 |
35 |
X = Area (square feet) (*100) |
9 |
15 |
10 |
11 |
10 |
a. The owner wants to forecast sales on the basis of the area. Which variable is the dependent variable? Which variable is the independent variable?
b. Determine the regression equation.
c. Interpret the values of the slope and the intercept.
d. Test the significance of the slope at 1% level of significance.
e. Determine the coefficient of correlation between the sales price and the area.
f. Interpret the strength of the correlation coefficient.
g. Determine the coefficient of determination and present its interpretation.
h. Determine the coefficient of non-determination.
SUMMARY OUTPUT |
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Regression Statistics |
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Multiple R |
0.969217713 |
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R Square |
0.939382976 |
|||||||
Adjusted R Square |
0.919177301 |
|||||||
Standard Error |
5.284339356 |
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Observations |
5 |
|||||||
ANOVA |
||||||||
df |
SS |
MS |
F |
Significance F |
||||
Regression |
1 |
1298.227 |
1298.227 |
46.49105 |
0.006453 |
|||
Residual |
3 |
83.77273 |
27.92424 |
|||||
Total |
4 |
1382 |
||||||
Coefficients |
Standard Error |
t Stat |
P-value |
Lower 95% |
Upper 95% |
Lower 95.0% |
Upper 95.0% |
|
Intercept |
-34.5 |
12.61619 |
-2.73458 |
0.071664 |
-74.6503 |
5.650339 |
-74.6503 |
5.650339 |
Area |
7.681818182 |
1.126625 |
6.818434 |
0.006453 |
4.096395 |
11.26724 |
4.096395 |
11.26724 |
a) The dependent variable is Sales price.
The independent variable is Area
b) The regression equation is = - 34.5 + 7.681818182*x
c) Interpretation of slope: Expected change in Sales by 7.681818182 when in area increases by one unit.
Interpretation of Intercept: The sales is - 34.5 when area = 0.
d) The null and alternative hypothesis is
Level of significance = 0.01
Test statistic for slope is t = 6.82 ( Given in output)
P-value = 0.006453
P-value < 0.01 we reject null hypothesis.
Conclusion: There is a good contribution of an area in a model.
e) Coefficient of correlation = r = 0.9692 ( Given in output)
f) There is the strong correlation between sales and area.
g) Coefficient of determination = = 0.9394
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