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  2. 68–95–99.7 rule - Wikipedia

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

    In statistics, the 68–95–99.7 rule, also known as the empirical rule, and sometimes abbreviated 3sr, is a shorthand used to remember the percentage of values that lie within an interval estimate in a normal distribution: approximately 68%, 95%, and 99.7% of the values lie within one, two, and three standard deviations of the mean, respectively.

  3. Circular error probable - Wikipedia

    en.wikipedia.org/wiki/Circular_error_probable

    CEP is not a good measure of accuracy when this distribution behavior is not met. Munitions may also have larger standard deviation of range errors than the standard deviation of azimuth (deflection) errors, resulting in an elliptical confidence region. Munition samples may not be exactly on target, that is, the mean vector will not be (0,0).

  4. Chebyshev's inequality - Wikipedia

    en.wikipedia.org/wiki/Chebyshev's_inequality

    In probability theory, Chebyshev's inequality (also called the Bienaymé–Chebyshev inequality) provides an upper bound on the probability of deviation of a random variable (with finite variance) from its mean. More specifically, the probability that a random variable deviates from its mean by more than is at most , where is any positive ...

  5. Three-point estimation - Wikipedia

    en.wikipedia.org/wiki/Three-point_estimation

    Three-point estimation. The three-point estimation technique is used in management and information systems applications for the construction of an approximate probability distribution representing the outcome of future events, based on very limited information. While the distribution used for the approximation might be a normal distribution ...

  6. Bessel's correction - Wikipedia

    en.wikipedia.org/wiki/Bessel's_correction

    Bessel's correction. In statistics, Bessel's correction is the use of n − 1 instead of n in the formula for the sample variance and sample standard deviation, [1] where n is the number of observations in a sample. This method corrects the bias in the estimation of the population variance. It also partially corrects the bias in the estimation ...

  7. Standard deviation - Wikipedia

    en.wikipedia.org/wiki/Standard_deviation

    The mean and the standard deviation of a set of data are descriptive statistics usually reported together. In a certain sense, the standard deviation is a "natural" measure of statistical dispersion if the center of the data is measured about the mean. This is because the standard deviation from the mean is smaller than from any other point.

  8. 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 ...

  9. Risk-neutral measure - Wikipedia

    en.wikipedia.org/wiki/Risk-neutral_measure

    If the interest rate R were not zero, we would need to discount the expected value appropriately to get the price. In particular, the portfolio consisting of each Arrow security now has a present value of 1 1 + R {\displaystyle {\frac {1}{1+R}}} , so the risk-neutral probability of state i becomes ( 1 + R ) {\displaystyle (1+R)} times the price ...