enow.com Web Search

Search results

1. Results from the WOW.Com Content Network

2. Unbiased estimation of standard deviation - Wikipedia

   en.wikipedia.org/wiki/Unbiased_estimation_of...

   One way of seeing that this is a biased estimator of the standard deviation of the population is to start from the result that s 2 is an unbiased estimator for the variance σ 2 of the underlying population if that variance exists and the sample values are drawn independently with replacement. The square root is a nonlinear function, and only ...

3. Bessel's correction - Wikipedia

   en.wikipedia.org/wiki/Bessel's_correction

   Firstly, while the sample variance (using Bessel's correction) is an unbiased estimator of the population variance, its square root, the sample standard deviation, is a biased estimate of the population standard deviation; because the square root is a concave function, the bias is downward, by Jensen's inequality.

4. Bias of an estimator - Wikipedia

   en.wikipedia.org/wiki/Bias_of_an_estimator

   The theory of median-unbiased estimators was revived by George W. Brown in 1947: [8]. An estimate of a one-dimensional parameter θ will be said to be median-unbiased, if, for fixed θ, the median of the distribution of the estimate is at the value θ; i.e., the estimate underestimates just as often as it overestimates.

5. Minimum-variance unbiased estimator - Wikipedia

   en.wikipedia.org/wiki/Minimum-variance_unbiased...

   However, the sample standard deviation is not unbiased for the population standard deviation – see unbiased estimation of standard deviation. Further, for other distributions the sample mean and sample variance are not in general MVUEs – for a uniform distribution with unknown upper and lower bounds, the mid-range is the MVUE for the ...

6. Fisher consistency - Wikipedia

   en.wikipedia.org/wiki/Fisher_consistency

   The sample mean is a Fisher consistent and unbiased estimate of the population mean, but not all Fisher consistent estimates are unbiased. Suppose we observe a sample from a uniform distribution on (0,θ) and we wish to estimate θ. The sample maximum is Fisher consistent, but downwardly biased. Conversely, the sample variance is an unbiased ...

7. Variance - Wikipedia

   en.wikipedia.org/wiki/Variance

   The unbiased estimation of standard deviation is a technically involved problem, though for the normal distribution using the term n − 1.5 yields an almost unbiased estimator. The unbiased sample variance is a U-statistic for the function ƒ(y 1, y 2) = (y 1 − y 2) 2 /2, meaning that it is obtained by averaging a 2-sample statistic over 2 ...

8. Algorithms for calculating variance - Wikipedia

   en.wikipedia.org/wiki/Algorithms_for_calculating...

   Based on this sample, the estimated population mean is 10, and the unbiased estimate of population variance is 30. Both the naïve algorithm and two-pass algorithm compute these values correctly. Next consider the sample (10 8 + 4, 10 8 + 7, 10 8 + 13, 10 8 + 16), which gives rise to the same estimated variance as the first sample. The two-pass ...

9. Lehmann–Scheffé theorem - Wikipedia

   en.wikipedia.org/wiki/Lehmann–Scheffé_theorem

   1.1 Proof. 2 Example for when ... is the uniformly minimum-variance unbiased estimator ... be a random sample from a distribution that has p.d.f (or p.m.f in the ...