TABLE 14-6
One of the Most Common Questions of Prospective

question 65

Multiple Choice

TABLE 14-6
One of the most common questions of prospective house buyers pertains to the average cost of heating in dollars (Y) . To provide its customers with information on that matter, a large real estate firm used the following 4 variables to predict heating costs: the daily minimum outside temperature in degrees of Fahrenheit (X₁) , the amount of insulation in inches (X₂) , the number of windows in the house (X₃) , and the age of the furnace in years (X₄) . Given below are the EXCEL outputs of two regression models.
$\begin{array}{ll}\text { Model } 1 \\\text { Regression Statistics } \\\hline \text { R Square }& 0.8080 \\\text { AdjustedR S quare }& 0.7568 \\\text { Observations } &20 \end{array}$

ANOVA
$\begin{array}{lrrccc} & \text { df } &{S S} & M S & F & \text { Signuficance F } \\\hline \text { Regression } & 4 & 169503.4241 & 42375.86 & 15.7874 & 2.96869 E-05 \\\text { Residual } & 15 & 40262.3259 & 2684.155 & & \\\text { Total } & 19 & 209765.75 & & & \\\hline\end{array}$

$\begin{array}{lrrrrrrr} && \text { Standard } & & \text {Lower} & \text {Upper }\\& \text {Coefficients} & \text {Error} & \text { t Stat } & \text {p -value} & 90.0 \% & 90.0 \% \\ \hline \text { Intercept }& 421.4277 & 77.8614 & 5.4125 & 7.2 \mathrm{E}-05& 284.9327 & 557.9227 \\ \text { X{1} (Temperature) } & -4.5098 & 0.8129 & -5.5476 &5.58 \mathrm{E}-05 & -5.9349 & -3.0847 \\ \text {X{2} (Insulation) }& -14.9029 & 5.0508 & -2.9505 & 0.0099 & -23.7573 & -6.0485 \\ \text { X{3} (Windows) }& 0.2151 & 4.8675 & 0.0442 & 0.9653 & -8.3181 & 8.7484 \\ \text { X{4} (Furnace Age) } & 6.3780 & 4.1026 & 1.5546 & 0.1408 & -0.8140 & 13.5702 \\\hline\end{array}$

$\begin{array}{ll} \text { Model 2} \\\hline \text {Regression Statistics} \\\hline \text {R Square }& 0.7768\\ \text {Adjusted R Square }&0.7506 \\ \text {Observations }& 20 \\\hline\end{array}$
ANOVA
$\begin{array}{lrrrcc}\hline & \text { d f} & \text { SS } & \text { MS } & \text {SS } & \text {Significance F } \\\hline \text {Regression} & 2 & 162958.2277 & 81479.11 & 29.5923 & 2.9036 \mathrm{E}-06 \\ \text {Residual }& 17 & 46807.5222 & 2753.384 & & \\ \text {Total }& 19 & 209765.75 & & & \\\hline\end{array}$

$\begin{array}{lcccccc} && \text { Standard } & &\text { Lower} &\text { Upper} \\& \text {Coefficients }&\text { Error }&\text { t Stat }& \text { p -value} &95 \%& 95 \% \\\hline \text {Intercept }& 489.3227 & 43.982611 .1253 &3.17 \mathrm{E}-09& 396.5273 & 582.1180 \\\text { X{1} (Temperature) }& -5.1103 & 0.6951-7.3515 & 1.13 \mathrm{E}-06 & -6.5769 & -3.6437 \\\text { X{2} (Insulation) }& -14.7195 & 4.8864-3.0123 & 0.0078 & -25.0290 & -4.4099 \\\hline\end{array}$

-Referring to Table 14-6, what can we say about Model 1?

Solve systems of linear inequalities.

Understand the role of the U.S. dollar in the international market.

Comprehend the structure and function of foreign exchange markets.

Grasp the essentials of currency conversion and exchange rate quotations.

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