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  2. Mode (statistics) - Wikipedia

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

    Like the statistical mean and median, the mode is a way of expressing, in a (usually) single number, important information about a random variable or a population. The numerical value of the mode is the same as that of the mean and median in a normal distribution, and it may be very different in highly skewed distributions.

  3. Median - Wikipedia

    en.wikipedia.org/wiki/Median

    The median of a Cauchy distribution with location parameter x 0 and scale parameter y is x 0, the location parameter. The median of a power law distribution x −a, with exponent a > 1 is 2 1/(a − 1) x min, where x min is the minimum value for which the power law holds [10] The median of an exponential distribution with rate parameter λ is ...

  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 ⁠ ⁠ (sigma).

  6. Probability density function - Wikipedia

    en.wikipedia.org/wiki/Probability_density_function

    This probability is given by the integral of this variable's PDF over that range—that is, it is given by the area under the density function but above the horizontal axis and between the lowest and greatest values of the range. The probability density function is nonnegative everywhere, and the area under the entire curve is equal to 1.

  7. 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)

  8. Average - Wikipedia

    en.wikipedia.org/wiki/Average

    If exactly one value is left, it is the median; if two values, the median is the arithmetic mean of these two. This method takes the list 1, 7, 3, 13 and orders it to read 1, 3, 7, 13. Then the 1 and 13 are removed to obtain the list 3, 7. Since there are two elements in this remaining list, the median is their arithmetic mean, (3 + 7)/2 = 5.

  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.