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  2. 68–95–99.7 rule - Wikipedia

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

    [2] In the social sciences, a result may be considered statistically significant if its confidence level is of the order of a two-sigma effect (95%), while in particle physics and astrophysics, there is a convention of requiring statistical significance of a five-sigma effect (99.99994% confidence) to qualify as a discovery. [3]

  3. Standard deviation - Wikipedia

    en.wikipedia.org/wiki/Standard_deviation

    where μ is the expected value of the random variables, σ equals their distribution's standard deviation divided by n 1 ⁄ 2, and n is the number of random variables. The standard deviation therefore is simply a scaling variable that adjusts how broad the curve will be, though it also appears in the normalizing constant .

  4. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    The value of the normal density is practically zero when the value lies more than a few standard deviations away from the mean (e.g., a spread of three standard deviations covers all but 0.27% of the total distribution).

  5. 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 ...

  6. Variance - Wikipedia

    en.wikipedia.org/wiki/Variance

    A square with sides equal to the difference of each value from the mean is formed for each value. Arranging the squares into a rectangle with one side equal to the number of values, n , results in the other side being the distribution's variance, σ 2 .

  7. 97.5th percentile point - Wikipedia

    en.wikipedia.org/wiki/97.5th_percentile_point

    "The value for which P = .05, or 1 in 20, is 1.96 or nearly 2; it is convenient to take this point as a limit in judging whether a deviation is to be considered significant or not." [11] In Table 1 of the same work, he gave the more precise value 1.959964. [12] In 1970, the value truncated to 20 decimal places was calculated to be

  8. Folded normal distribution - Wikipedia

    en.wikipedia.org/wiki/Folded_normal_distribution

    We start with an initial value for and find the positive root of the last equation. Then, we get an updated value of σ 2 {\displaystyle \sigma ^{2}} . The procedure is being repeated until the change in the log-likelihood value is negligible.

  9. Log-normal distribution - Wikipedia

    en.wikipedia.org/wiki/Log-normal_distribution

    A probability distribution is not uniquely determined by the moments E[X n] = e nμ + ⁠ 1 / 2 ⁠ n 2 σ 2 for n ≥ 1. That is, there exist other distributions with the same set of moments. [4] In fact, there is a whole family of distributions with the same moments as the log-normal distribution. [citation needed]