[Numpy-tickets] [NumPy] #502: Unbiased estimates of variance/ std deviation

[NumPy]

#502: Unbiased estimates of variance/ std deviation
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 Reporter:  pierregm     |        Owner:  somebody
     Type:  enhancement  |       Status:  new     
 Priority:  low          |    Milestone:  1.1     
Component:  Other        |      Version:  none    
 Severity:  trivial      |   Resolution:          
 Keywords:               |  
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Comment (by rkern):

 My preference is to not use the term "bias," since it's wrong. The
 standard definition of bias, E[X-Xtrue], is inappropriate for quantities
 like variance and standard deviation. Notably, the square root of the N-1,
 "unbiased" variance is *not* an unbiased estimate of the standard
 deviation. Using an appropriate definition of bias, E[log(X/Xtrue)], does
 give coherent estimates of variance and standard deviation. However, the
 factor is N-2, not N-1.

 My preference is to add a parameter that is subtracted from N rather than
 a flag that switches between N and N-1. The shortest name a I can come up
 with is a bit obscure, though, "ddof" for "change in degrees of freedom".

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Ticket URL: <http://projects.scipy.org/scipy/numpy/ticket/502#comment:3>
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