Second-order uncertainty


Those not trained in statistics often find the expression 'stable random process' quite puzzling. "How", they ask, "can a process be both stable and random?" The answer, of course, is that any one draw is random and, hence, unknowable in advance. If the random process is stable, however, then sizeable samples will exhibit broadly similar characteristics, such as the mean, the dispersion (standard deviation), the degree of symmetry or lack thereof (skewness), and the tendency for probability in

Only users who have a paid subscription or are part of a corporate subscription are able to print or copy content.

To access these options, along with all other subscription benefits, please contact [email protected] or view our subscription options here:

You are currently unable to copy this content. Please contact [email protected] to find out more.

To continue reading...

You need to sign in to use this feature. If you don’t have a account, please register for a trial.

Sign in
You are currently on corporate access.

To use this feature you will need an individual account. If you have one already please sign in.

Sign in.

Alternatively you can request an individual account here: