The general " M "-sample variance remains important since it allows dead time in measurements and bias functions allows conversion into Allan variance values.
42.
The 2-sample variance case is a special case of the " M "-sample variance which produces an average of the frequency derivative.
43.
The 2-sample variance case is a special case of the " M "-sample variance which produces an average of the frequency derivative.
44.
Since the square root is a strictly concave function, it follows from Jensen's inequality that the square root of the sample variance is an underestimate.
45.
Most simply, the sample variance is computed as an average of squared deviations about the ( sample ) mean, by dividing by " n ."
46.
If this is done, it is common to use n-1 as the divisor rather than n, corresponding to an unbiased estimate of the sample variance.
47.
An example of this is to show that the sample mean and sample variance of a normal distribution are independent statistics, which is done in the Example section below.
48.
It however laid the foundation for using the 2-sample variance as the base case of comparison among other variants of the " M "-sample variance.
49.
It however laid the foundation for using the 2-sample variance as the base case of comparison among other variants of the " M "-sample variance.
50.
The remaining two parameters \ hat { a }, \ hat { c } can be determined using the sample mean and the sample variance using a variety of equations.
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