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SCENARIO 13-6
One of the Most Common Questions of Prospective

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SCENARIO 13-6
One of the most common questions of prospective house buyers pertains to the cost of heating in dollars (Y).To provide its customers with information on that matter, a large real estate firm used the following 2 variables to predict heating costs: the daily minimum outside temperature in degrees of Fahrenheit ( X1 ) and the amount of insulation in inches ( X 2 ).Given below is EXCEL output of the regression model.  Regression Statistics  Multiple R 0.5270 R Square 0.2778 Adjusted R Square 0.1928 Standard Error 40.9107 Observations 20\begin{array}{l}\begin{array} { l r } \hline { \text { Regression Statistics } } \\\hline \text { Multiple R } & 0.5270 \\\text { R Square } & 0.2778 \\\text { Adjusted R Square } & 0.1928 \\\text { Standard Error } & 40.9107 \\\text { Observations } & 20 \\\hline\end{array}\\\end{array}
 ANOVA  df  SS  MS F Significance F  Regression 210943.01905471.50953.26910.0629 Residual 1728452.60271673.6825 Total 1939395.6218\begin{array}{lrrrrr}\text { ANOVA }\\\hline&\text { df } & \text { SS } & \text { MS } & F & \text { Significance F }\\\hline\text { Regression } & 2 & 10943.0190 & 5471.5095 & 3.2691 & 0.0629 \\\text { Residual } & 17 & 28452.6027 & 1673.6825 & & \\\text { Total } & 19 & 39395.6218 & & &\end{array} 13-22 Multiple Regression  Coefficients  Standard Error  t Stat  P-volue  Lower 95%  Upper 95%  Intercept 448.292590.78534.93790.0001256.7522639.8328 Temperature 2.76211.23712.23270.03935.37210.1520 Insulation 15.940810.06381.58400.131637.17365.2919 Also SSR(X1X2)=8343.3572 and SSR(X2X1)=4199.2672\begin{array}{l}\begin{array} { l r r r r r r } \hline & \text { Coefficients } &{ \text { Standard Error } } & { \text { t Stat } } & \text { P-volue } & \text { Lower 95\% } & \text { Upper 95\% } \\\hline \text { Intercept } & 448.2925 & 90.7853 & 4.9379 & 0.0001 & 256.7522 & 639.8328 \\\text { Temperature } & - 2.7621 & 1.2371 & - 2.2327 & 0.0393 & - 5.3721 & - 0.1520 \\\text { Insulation } & - 15.9408 & 10.0638 & - 1.5840 & 0.1316 & - 37.1736 & 5.2919 \\\hline\end{array}\\\text { Also } \operatorname { SSR } \left( X _ { 1 } \mid X _ { 2 } \right) = 8343.3572 \text { and } \operatorname { SSR } \left( X _ { 2 } \mid X _ { 1 } \right) = 4199.2672\end{array}
-Referring to SCENARIO 13-6, the partial F test forH0: Variable X2 does not significantly improve the model after variable X1 has been includedH1: Variable X2 significantly improves the model after variable X1 has been included has and degrees of freedom.


Definitions:

Empirical Approach

A method of acquiring knowledge based on observation, experimentation, and evidence rather than theories or pure logic.

Examine Assumptions

The process of critically questioning and evaluating the underlying beliefs or principles that are taken for granted in arguments, theories, or policies.

Observation

The action or process of observing something or someone carefully or in order to gain information.

Evidence-Based Method

A process of making decisions and taking actions based on the best current scientific evidence, typically applied in fields like medicine, psychology, and education.

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