Reducing Sample Size by 1 When Computing Variance

A population has extreme large and small values that are less likely to be included in a sample (for bell-like distributions, anyway). So a sample you collect will usually be biased towards the mean, which underestimtes the SD and variance.
What I don’t know is: whether n-1 is derived from some mathematical principle or if it’s just a makeshift adjustment that everyone does to ‘fix’ the bias… anyone know?
 
oktavian wrote:What I don’t know is: whether n-1 is derived from some mathematical principle or if it’s just a makeshift adjustment that everyone does to ‘fix’ the bias… anyone know?
It is derived from a mathematical principle: dividing by n – 1 ensures that the expected value of the (bias-adjusted) sample standard deviation equals the population standard deviation.
 
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