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 used to determine whether

A) an estimated slope coefficient is different for different subsamples of the data.
B) a subset of independent variables is jointly significant.
C) estimated sample regression functions are different for two different subsamples of the data.
D) a subset of estimated slope coefficients is jointly significant for two different subsamples of the data.