A small random variance or a bunch of uncorrelated errors ought to produce something very similar to a normal distribution, which we can model with random generation.
The Nelson rules are basically an attempt to determine whether relatively 'healthy' data is actually coming from some specific forcing events (e.g. oscillation instead of random variance), so it looks for breaks with normal distributions.
The Nelson rules are basically an attempt to determine whether relatively 'healthy' data is actually coming from some specific forcing events (e.g. oscillation instead of random variance), so it looks for breaks with normal distributions.