A real estate builder wishes to determine how house size (House) is influenced by family income (Income) and family size (Size). House size is measured in meter square and income is measured in IDR...





A real estate builder wishes to determine how house size (House) is influenced by family income (Income) and family size (Size). House size is measured in meter square and income is measured in IDR millions. The builder randomly selected 50 families and ran the multiple regression. Partial Microsoft Excel output is provided below:








  1. What is the population model of this regression problem?




  2. What is the sample estimates of the regression problem?




  3. Which of the independent variables in the model are significant at the 5% level?


    Formulate the hypothesis and explain the answer.











Regression Statistics<br>Multiple R<br>0.8479<br>R Square<br>0.7189<br>Adjusted R Square<br>0.7069<br>Standard Error<br>17.5571<br>Observations<br>50<br>ANOVA<br>df<br>SS<br>MS<br>F<br>Significance F<br>Regression<br>37043.3236<br>18521.6618<br>0.0000<br>Residual<br>14487.7627<br>308.2503<br>Total<br>49<br>51531.0863<br>Coefficients<br>Standard Error<br>t Stat<br>P-value<br>Intercept<br>-5.5146<br>7.2273<br>-0.7630<br>0.4493<br>Income<br>0.4262<br>0.0392<br>10.8668<br>0.0000<br>Size<br>5.5437<br>1.6949<br>3.2708<br>0.0020<br>

Extracted text: Regression Statistics Multiple R 0.8479 R Square 0.7189 Adjusted R Square 0.7069 Standard Error 17.5571 Observations 50 ANOVA df SS MS F Significance F Regression 37043.3236 18521.6618 0.0000 Residual 14487.7627 308.2503 Total 49 51531.0863 Coefficients Standard Error t Stat P-value Intercept -5.5146 7.2273 -0.7630 0.4493 Income 0.4262 0.0392 10.8668 0.0000 Size 5.5437 1.6949 3.2708 0.0020

Jun 07, 2022
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