Figure
Suppose That in the Course of Testing Whether Age

Figure
Suppose that in the course of testing whether Age and Family Size are jointly significant,you estimate the results in Figure 6.3. $\begin{array}{lc}\text { SUMMARY OUTPUT }\\\\\\\hline\text { Regrestion Starittict } & \\\hline \text { Muftiple R. } & 0.070494476 \\\text { R Sequrt } & 0.004969471 \\\text { Adigated R. Square } & 0.001879314 \\\text { Standard Esror } & 4.819403326 \\\text { Observations } & 970 \\\hline\end{array}$



$\begin{array}{l}\text { ANOVA }\\\begin{array}{lccccc}\hline & d f & S 5 & M S & F & \text { Signifieance } F \\\hline \text { Regranion } & 3 & 112.0566012 & 37.3522004 & 1.608161442 & 0.185858614 \\\text { Reaidual } & 966 & 22436.94237 & 23.22664841 & & \\\text { Total } & 969 & 22548.99897 & & & \\\hline\end{array}\end{array}$


$\begin{array}{lcccccc}\hline & \text { Coeffeientt } & \text { Srandard Error } & \text { t Stat } & \text { P-value } & \text { Lower } 9596 & \text { Upper } 9596 \\\hline \text { Intercept } & 4.049920982 & 1.042107341 & 3.886280064 & 0.000108739 & 2.004865844 & 6.094976119 \\\text { Age } & 0.015626984 & 0.010365497 & 1.507396119 & 0.131984878 & -0.004714504 & 0.035968471 \\\text { Family Size } & -0.093093463 & 0.084602383 & -1.100364552 & 0.271447442 & -0.259119103 & 0.072932177 \\\text { Years of Education } & 0.005642075 & 0.06474525 & 0.087142685 & 0.930576157 & -0.121415476 & 0.132699626 \\\hline\end{array}$

$\text { SUMALARY OUTPUT }$

$\begin{array}{lc}\hline \text { Regrestion Staritticz } & \\\hline \text { Multiple R. } & 0.005034034 \\\text { R Square } & 2.53415 \mathrm{E}-05 \\\text { Adjuted R. Square } & -0.00100769 \\\text { Standard Error } & 4.826368211 \\\text { Observations } & 970 \\\hline\end{array}$$0.115170636$


$\begin{array}{l}\text { ANOVA }\\\begin{array}{lccccc}\hline & d f & S S & M S & F & \text { Signffeance } F \\\hline \text { Regresion } & 1 & 0.571425385 & 0.571425385 & 0.024531191 & 0.875573561 \\\text { Reiidual } & 968 & 22548.42754 & 23.29383011 & & \\\text { Total } & 969 & 22548.99897 & & & \\\hline\end{array}\end{array}$

$\begin{array}{l}\begin{array}{lcccccc}\hline & \text { Coefficienty } & \text { Standard Emor } & \text { t Star } & \text { P-value } & \text { Lower } 9596 & \text { Upper } 9596 \\\hline \text { Intercept } & 4.288825645 & 0.732966216 & 5.851327866 & 6.66867 E-09 & 2.850439806 & 5.727211483 \\\text { Years of Education } & 0.009850586 & 0.062893064 & 0.156624361 & 0.875573561 & -0.113571873 & 0.133273045 \\\hline\end{array}\\\text { Figure } 6.3\end{array}$
-Chow tests are based on comparing the

A) sum of the unexplained sums of squares added together from separate regressions to the unexplained sum of squares for the pooled regression.
B) unexplained sums of squares from separate regressions to each other.
C) sum of the explained sums of squares from separate regressions to the explained sum of squares for the pooled regression.
D) explained sums of squares from separate regressions to each other.