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SUMMARY OUTPUT
Regression Statistics
Multiple R
0.786816411
R Square
0.619080065
Adjusted R Square
0.585469483
Standard Error
180042.1358
Observations
38
ANOVA
df
SS
MS
F
Significance F
Regression
3
1.79118E+12
5.97E+11
18.4192
2.84688E-07
Residual
34
1.10212E+12
3.24E+10
Total
37
2.8933E+12
Coefficients
t Stat
P-value
Lower 95%
Upper 95%
Lower 95.0%
Upper 95.0%
Intercept
723745.5192
164737.5271
4.393325
0.000104
388958.5842
1058532.454
Lot Sqft
24.34247836
6.780755687
3.589936
0.00103
10.56232484
38.12263187
Age
-6229.29051
1541.071989
-4.04218
0.000287
-9361.125599
-3097.455421
°-3097.455421
Bedrooms
61682.63944
30558.60758
2.018503
0.051483
-419.923028
123785.2019
RESIDUAL OUTPUT
PROBABILITY OUTPUT
Observation
Predicted Sold Price
Residuals
Percentile
Sold Price
1
1091003.519
58996.48065
1.315789
400000
2
942238.6536
-403238.6536
3.947368
621964.8781
58035.12194
6.578947
425000
4
614492.2402
-189492.2402
9.210526
430000
5
711627.0639
237372.9361
11.84211
500000
6
643715.134
-9015.133961
14.47368
539000
7
704715.0008
-204715.0008
17.10526
630000
8
739933.7991
60066.20094
19.73684
634700
1. Write the equation
2. Do the signs of the coefficients make sense?
3. Interpretation of the coefficients
4. Are the coefficients statistically significant?
5. Interpret R square
6. Is R square good/bad?
7. Is the equation as a whole statistically significant?
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