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  2. Standard deviation - Wikipedia

    en.wikipedia.org/wiki/Standard_deviation

    The formula for the population standard deviation (of a finite population) can be applied to the sample, using the size of the sample as the size of the population (though the actual population size from which the sample is drawn may be much larger).

  3. Unbiased estimation of standard deviation - Wikipedia

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

    Bias in standard deviation for autocorrelated data. The figure shows the ratio of the estimated standard deviation to its known value (which can be calculated analytically for this digital filter), for several settings of α as a function of sample size n. Changing α alters the variance reduction ratio of the filter, which is known to be

  4. Variance - Wikipedia

    en.wikipedia.org/wiki/Variance

    The red population has mean 100 and variance 100 (SD=10) while the blue population has mean 100 and variance 2500 (SD=50) where SD stands for Standard Deviation. In probability theory and statistics , variance is the expected value of the squared deviation from the mean of a random variable .

  5. 68–95–99.7 rule - Wikipedia

    en.wikipedia.org/wiki/68–95–99.7_rule

    The "68–95–99.7 rule" is often used to quickly get a rough probability estimate of something, given its standard deviation, if the population is assumed to be normal. It is also used as a simple test for outliers if the population is assumed normal, and as a normality test if the population is potentially not normal.

  6. 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.

  7. Deviation (statistics) - Wikipedia

    en.wikipedia.org/wiki/Deviation_(statistics)

    Standard deviation is a widely used measure of the spread or dispersion of a dataset. It quantifies the average amount of variation or deviation of individual data points from the mean of the dataset. It uses squared deviations, and has desirable properties. Standard deviation is sensitive to extreme values, making it not robust. [7]

  8. Sample size determination - Wikipedia

    en.wikipedia.org/wiki/Sample_size_determination

    For instance, if estimating the effect of a drug on blood pressure with a 95% confidence interval that is six units wide, and the known standard deviation of blood pressure in the population is 15, the required sample size would be =, which would be rounded up to 97, since sample sizes must be integers and must meet or exceed the calculated ...

  9. Statistical dispersion - Wikipedia

    en.wikipedia.org/wiki/Statistical_dispersion

    The blue population is much more dispersed than the red population. In statistics, dispersion (also called variability, scatter, or spread) is the extent to which a distribution is stretched or squeezed. [1] Common examples of measures of statistical dispersion are the variance, standard deviation, and interquartile range. For instance, when ...