b)
Let us assume \({X_1}\;,\;{X_2}\) random variables \({X_1}(i,j) = i\;,\;{X_2}(i,j) = j\).
Here \({X_1}\) is the number appearing on the first die and \({X_2}\) is the number appearing on the second die.
\(\begin{aligned}{}E\left( {{X_1}^2} \right) &= \frac{1}{{12}}\left( {{1^2} + {2^2} + {3^2} + {4^2} + {5^2} + \ldots \ldots . + {{12}^2}} \right)\\E\left( {{X_1}^2} \right) &= \frac{{325}}{6}\end{aligned}\)
Variance can be determined as:
\(\begin{aligned}{}V({X_1}) &= E\left( {{X_1}^2} \right) - E\left( {\begin{aligned}{*{20}{c}}X\\1\end{aligned}} \right.\\V({X_1}) &= \frac{{325}}{6} - {()^{\frac{{13}}{2}}}\\V({X_1}) &= \frac{{325}}{6} - \frac{{13}}{2}\\V({X_1}) &= \frac{{143}}{{12}}\end{aligned}\)
Therefore, \(V(X1) = V(X2) = \frac{{143}}{{12}}\).
Sum of variances is given as:
\(\begin{aligned}{}V(X) &= V({X_1}) + V({X_2})\\V(X) &= \frac{{143}}{{12}} + \frac{{143}}{{12}}\\V(X) &= \frac{{143}}{6}\end{aligned}\)
Therefore, the variance of the sum of the numbers that comes up is \(\frac{{143}}{6}\).