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  2. Median - Wikipedia

    en.wikipedia.org/wiki/Median

    The median of a normal distribution with mean μ and variance σ 2 is μ. In fact, for a normal distribution, mean = median = mode. The median of a uniform distribution in the interval [a, b] is (a + b) / 2, which is also the mean. The median of a Cauchy distribution with location parameter x 0 and scale parameter y is x 0, the location parameter.

  3. Mode (statistics) - Wikipedia

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

    The median is also very robust in the presence of outliers, while the mean is rather sensitive. In continuous unimodal distributions the median often lies between the mean and the mode, about one third of the way going from mean to mode. In a formula, median ≈ (2 × mean + mode)/3.

  4. Log-normal distribution - Wikipedia

    en.wikipedia.org/wiki/Log-normal_distribution

    Comparison of mean, median and mode of two log-normal distributions with different skewness. The mode is the point of global maximum of the probability density function. In particular, by solving the equation ( ln ⁡ f ) ′ = 0 {\displaystyle (\ln f)'=0} , we get that:

  5. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    The parameter is the mean or expectation of the distribution (and also its median and mode), while the parameter is the variance. The standard deviation of the distribution is σ {\textstyle \sigma } (sigma).

  6. Central tendency - Wikipedia

    en.wikipedia.org/wiki/Central_tendency

    the point minimizing the sum of distances to a set of sample points. This is the same as the median when applied to one-dimensional data, but it is not the same as taking the median of each dimension independently. It is not invariant to different rescaling of the different dimensions. Quadratic mean (often known as the root mean square)

  7. Continuous uniform distribution - Wikipedia

    en.wikipedia.org/wiki/Continuous_uniform...

    The midpoint of the distribution, +, is both the mean and the median of the uniform distribution. Although both the sample mean and the sample median are unbiased estimators of the midpoint, neither is as efficient as the sample mid-range , i.e. the arithmetic mean of the sample maximum and the sample minimum, which is the UMVU estimator of the ...

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  9. Median absolute deviation - Wikipedia

    en.wikipedia.org/wiki/Median_absolute_deviation

    The median absolute deviation is a measure of statistical dispersion. Moreover, the MAD is a robust statistic , being more resilient to outliers in a data set than the standard deviation . In the standard deviation, the distances from the mean are squared, so large deviations are weighted more heavily, and thus outliers can heavily influence it.