Examine the below output on how the Price of a house is depenent on the followin

Question

Examine the below output on how the Price of a house is depenent on the following indepenent variables.

"P"= price, "BE" = Bedrooms, "BA" = Bathrooms, "N"= Neighborhood.

What is the final eqution?

Interpretation of regression coefficients.

Is this model linear?

. regress P BE BA N Source df MS 43 37.74 0.0000 0.7438 0.7241 41.623 Number of obs F (3, 39) 196160.737 67566.3332 Model 3 65386.9122 Prob > F Residual 39 1732.47008 R-squared Adj R-squared = Total 263727.07 42 6279.21595 Root MSE Coef . Std. Err t >It [95% Conf . Interval] 34.89926 11.94314 60.12893 16.22604 -32.76155 8.822845 101.5891 42.56501 2.92 0.006 3.71 0.001 -3.71 0.001 2.39 0.022 BE 59.05654 92.9492 -50.60744 -14.91567 187.6849 10.74197 BA 27.30866 cons 15.49323

Explanation / Answer

The final linear regression equation is : Price = 34.89926 * BE + 60.12893 * BA - 32.76155 * N + 1015891

Interpretation of regression coefficients :

Price and Bedroom are positively related . Price increases by 34.89926 units change in bedroom .

Price and Bathroom are positively related . Price increases by 60.12893 units change in bathroom .

Price and Neighborhood are negatively related . Price decreases by 32.76155 units change in neighborhood .

Model is linear : At 5 % level of significance the p-value (column P>|t|) for bedroom , bathroom and neighborhood is less than 0.05 hence we can say that model is linear .

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