Suppose I have a method that I can use to generate $n_p$ signals (we can intend them as realizations of an unknown not stationary discrete-time stochastic process). Modifying the method, I can obtain other $n_p$ signals.
I'd like to quantify the "variability" of the several group of $n_p$ generated signals.
The procedure I am using is the following: For each time step I have $n_p$ values and I compute the Interquartile Range (IQR). At this point I compute the average of the IQRs in order to obtain a single value that I can associate to that trial. Another approach is substituting the IQR with the range between 2.5th quantile and 97.5th quantile, but the procedure is the same.
Is this procedure correct? Does exist other more rigorous or correct way to quantify the global variability of the bunch of signals I have generated?
A related question is: variability among signals