We define also the sample variance \( \sigma^2 \) of all \( mn \) individual experiments as $$ \begin{equation} \sigma^2=\frac{1}{mn}\sum_{\alpha=1}^m\sum_{k=1}^n (x_{\alpha,k}-\langle X_m \rangle)^2. \tag{10} \end{equation} $$

These quantities, being known experimental values or the results from our calculations, may differ, in some cases significantly, from the similarly named exact values for the mean value \( \mu_X \), the variance \( \mathrm{Var}(X) \) and the covariance \( \mathrm{Cov}(X,Y) \).