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[ferret_users] Sample variance and computing running variance

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,

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