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