Given that the vectors \( \vec{a} + \vec{b} \) and \( \vec{a} - \vec{b} \) are mutually perpendicular, we have:
\[ (\vec{a} + \vec{b}) \cdot (\vec{a} - \vec{b}) = 0. \]
Expanding this, we get:
\[ \vec{a} \cdot \vec{a} - \vec{b} \cdot \vec{b} = 0. \]
Calculating \( \vec{a} \cdot \vec{a} \) and \( \vec{b} \cdot \vec{b} \):
\[ \vec{a} \cdot \vec{a} = (1)^2 + (\lambda)^2 + (-3)^2 = 1 + \lambda^2 + 9 = \lambda^2 + 10. \]
\[ \vec{b} \cdot \vec{b} = (3)^2 + (-1)^2 + (2)^2 = 9 + 1 + 4 = 14. \]
Setting \( \vec{a} \cdot \vec{a} = \vec{b} \cdot \vec{b} \):
\[ \lambda^2 + 10 = 14. \]
\[ \lambda^2 = 4. \]
\[ \lambda = 2 \quad (\text{since } \lambda > 0). \]
Now, calculate \( \vec{a} \cdot \vec{b} \) to find \( \cos \theta \):
\[ \vec{a} \cdot \vec{b} = (1)(3) + (2)(-1) + (-3)(2) = 3 - 2 - 6 = -5. \]
The magnitudes are:
\[ |\vec{a}| = \sqrt{1^2 + 2^2 + (-3)^2} = \sqrt{1 + 4 + 9} = \sqrt{14}. \]
\[ |\vec{b}| = \sqrt{3^2 + (-1)^2 + 2^2} = \sqrt{9 + 1 + 4} = \sqrt{14}. \]
Thus,
\[ \cos \theta = \frac{\vec{a} \cdot \vec{b}}{|\vec{a}| |\vec{b}|} = \frac{-5}{14}. \]
Now, we need to find \( (14 \cos \theta)^2 \):
\[ (14 \cos \theta)^2 = \left(14 \times \frac{-5}{14}\right)^2 = (-5)^2 = 25. \]
If \( X \) is a random variable such that \( P(X = -2) = P(X = -1) = P(X = 2) = P(X = 1) = \frac{1}{6} \), and \( P(X = 0) = \frac{1}{3} \), then the mean of \( X \) is