If you choose 0.05 for TOL, you should expect 5 or so bad bins per
trial from a histogram with 100 channels.
For monitoring, you must compromise
between the number of false messages you can tolerate (based on the total
number of channels you monitor), and the amount of data you will need to
collect to claim a channel is bad.
In general, a somewhat smaller fraction of
channels than TOL will be flagged as bad,
since for discrete distributions
(Poisson statistics), the probability is quantized.
For example, the probability might be 0.053 for 4 entries, and 0.021 for 3.
If TOL=0.05, only bins with 3 or fewer entries would be flagged as bad.