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  2. Unbiased estimation of standard deviation - Wikipedia

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

    Unbiased estimation of standard deviation. In statistics and in particular statistical theory, unbiased estimation of a standard deviation is the calculation from a statistical sample of an estimated value of the standard deviation (a measure of statistical dispersion) of a population of values, in such a way that the expected value of the ...

  3. Coefficient of variation - Wikipedia

    en.wikipedia.org/wiki/Coefficient_of_variation

    The coefficient of variation (CV) is defined as the ratio of the standard deviation to the mean , [1] It shows the extent of variability in relation to the mean of the population. The coefficient of variation should be computed only for data measured on scales that have a meaningful zero (ratio scale) and hence allow relative comparison of two ...

  4. Geometric standard deviation - Wikipedia

    en.wikipedia.org/wiki/Geometric_standard_deviation

    The geometric standard deviation is used as a measure of log-normal dispersion analogously to the geometric mean. [3] As the log-transform of a log-normal distribution results in a normal distribution, we see that the geometric standard deviation is the exponentiated value of the standard deviation of the log-transformed values, i.e. = ⁡ (⁡ (⁡)).

  5. Standard error - Wikipedia

    en.wikipedia.org/wiki/Standard_error

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  6. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    If is a standard normal deviate, then = + will have a normal distribution with expected value and standard deviation . This is equivalent to saying that the standard normal distribution Z {\textstyle Z} can be scaled/stretched by a factor of σ {\textstyle \sigma } and shifted by μ {\textstyle \mu } to yield a different normal distribution ...

  7. Student's t-distribution - Wikipedia

    en.wikipedia.org/wiki/Student's_t-distribution

    In probability theory and statistics, Student's t distribution (or simply the t distribution) is a continuous probability distribution that generalizes the standard normal distribution. Like the latter, it is symmetric around zero and bell-shaped. However, has heavier tails and the amount of probability mass in the tails is controlled by the ...

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