Dear ferret users,
I have 2 questions regarding computing variance.
1. sample and population based variance (
equivalently standard deviation):
I have noticed that stat command gives standard
deviation based on a sample where as var command gives
variance based on a population. My assumption is its
customary to calculate sample based variance unless
otherwise stated but why does ferret compute variance based
on population with var command? I think it is possible to
get sample based variance e.g. for my 1-D data with
l=140
list/precision=6 v1[l=@var]*v1[l=@ngd]/(v1[l=@ngd]-1) ! = 7005.65 (this is still slightly
different from sample based variance computed from other
method e.g. excel gave 7002.42 )
Isn't there a way to compute sample based variance in more
straight forward manner and why its not the default option
(with var)?
2. Computing running variance:
I am using boxcar smoother transformation (e.g.
v1[l=1:140@sbx:31]) to compute running mean but I can't think
of a way to compute running variance (standard deviation) in
similar manner. My guess is this would involve looping over
time but I am not able to work out a way.
Please advice. Thanks in advance.
Best regards,
Jagadish