Question 1 SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard 0.999666 0.999333 0.999307 Error Observations 39.51247 54 ANOVA Significance F Df S MS F Regression...





Estimate the model parameters using the method of least squares (from Excel output) and state the estimated model equation.





Question 1<br>SUMMARY OUTPUT<br>Regression Statistics<br>Multiple R<br>R Square<br>Adjusted R<br>Square<br>Standard<br>0.999666<br>0.999333<br>0.999307<br>Error<br>Observations<br>39.51247<br>54<br>ANOVA<br>Significance<br>F<br>Df<br>S<br>MS<br>F<br>Regression<br>Residual<br>2 1.19E+08 59656970 38211.39<br>1.03E-81<br>51<br>79622.99<br>1561.235<br>Total<br>53<br>1.19E+08<br>Standard<br>Upper<br>95%<br>Lower<br>95.0%<br>Upper<br>95.0%<br>Coefficients<br>Error<br>t Stat<br>P-value<br>Lower 95%<br>15.44438<br>Intercept<br>Reall income<br>Real Wealth<br>-9.71491<br>12.53213<br>-0.7752 0.441801<br>-34.8742 15.44438<br>-34.8742<br>0.726461<br>0.01399<br>51.92536<br>7.96E-46<br>0.698374 0.754548<br>0.698374 0.754548<br>0.036411<br>0.002589<br>14.06532<br>3.48E-19<br>0.031214 0.041608 0.031214 0.041608<br>

Extracted text: Question 1 SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard 0.999666 0.999333 0.999307 Error Observations 39.51247 54 ANOVA Significance F Df S MS F Regression Residual 2 1.19E+08 59656970 38211.39 1.03E-81 51 79622.99 1561.235 Total 53 1.19E+08 Standard Upper 95% Lower 95.0% Upper 95.0% Coefficients Error t Stat P-value Lower 95% 15.44438 Intercept Reall income Real Wealth -9.71491 12.53213 -0.7752 0.441801 -34.8742 15.44438 -34.8742 0.726461 0.01399 51.92536 7.96E-46 0.698374 0.754548 0.698374 0.754548 0.036411 0.002589 14.06532 3.48E-19 0.031214 0.041608 0.031214 0.041608

Jun 01, 2022
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