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  2. Sample mean and covariance - Wikipedia

    en.wikipedia.org/wiki/Sample_mean_and_covariance

    The sample mean ¯ (the arithmetic mean of a sample of values drawn from the population) makes a good estimator of the population mean, as its expected value is equal to the population mean (that is, it is an unbiased estimator). The sample mean is a random variable, not a constant, since its calculated value will randomly differ depending on ...

  3. Bias of an estimator - Wikipedia

    en.wikipedia.org/wiki/Bias_of_an_estimator

    The sample mean, on the other hand, is an unbiased [5] estimator of the population mean μ. [3] Note that the usual definition of sample variance is = = (¯), and this is an unbiased estimator of the population variance.

  4. Unbiased estimation of standard deviation - Wikipedia

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

    which is an unbiased estimator of the variance of the mean in terms of the observed sample variance and known quantities. If the autocorrelations are identically zero, this expression reduces to the well-known result for the variance of the mean for independent data. The effect of the expectation operator in these expressions is that the ...

  5. Standard error - Wikipedia

    en.wikipedia.org/wiki/Standard_error

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  6. Sampling bias - Wikipedia

    en.wikipedia.org/wiki/Sampling_bias

    In statistics, sampling bias is a bias in which a sample is collected in such a way that some members of the intended population have a lower or higher sampling probability than others. It results in a biased sample [1] of a population (or non-human factors) in which all individuals, or instances, were not equally likely to have been selected. [2]

  7. Estimator - Wikipedia

    en.wikipedia.org/wiki/Estimator

    A desired property for estimators is the unbiased trait where an estimator is shown to have no systematic tendency to produce estimates larger or smaller than the provided probability. Additionally, unbiased estimators with smaller variances are preferred over larger variances because it will be closer to the "true" value of the parameter.

  8. Bessel's correction - Wikipedia

    en.wikipedia.org/wiki/Bessel's_correction

    ¯ is the sample mean; σ 2 is the population variance; s n 2 is the biased sample variance (i.e., without Bessel's correction) s 2 is the unbiased sample variance (i.e., with Bessel's correction) The standard deviations will then be the square roots of the respective variances.

  9. 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 ...