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  2. Median - Wikipedia

    en.wikipedia.org/wiki/Median

    Calculating the median in data sets of odd (above) and even (below) observations. The median of a set of numbers is the value separating the higher half from the lower half of a data sample, a population, or a probability distribution. For a data set, it may be thought of as the “middle" value.

  3. Median test - Wikipedia

    en.wikipedia.org/wiki/Median_test

    Median test (also Mood’s median-test, Westenberg-Mood median test or Brown-Mood median test) is a special case of Pearson's chi-squared test. It is a nonparametric test that tests the null hypothesis that the medians of the populations from which two or more samples are drawn are identical. The data in each sample are assigned to two groups ...

  4. Hodges–Lehmann estimator - Wikipedia

    en.wikipedia.org/wiki/Hodges–Lehmann_estimator

    In statistics, the Hodges–Lehmann estimator is a robust and nonparametric estimator of a population's location parameter.For populations that are symmetric about one median, such as the Gaussian or normal distribution or the Student t-distribution, the Hodges–Lehmann estimator is a consistent and median-unbiased estimate of the population median.

  5. 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.

  6. Concentration of measure - Wikipedia

    en.wikipedia.org/wiki/Concentration_of_measure

    The concentration of measure phenomenon was put forth in the early 1970s by Vitali Milman in his works on the local theory of Banach spaces, extending an idea going back to the work of Paul Lévy. [ 2 ] [ 3 ] It was further developed in the works of Milman and Gromov , Maurey , Pisier , Schechtman , Talagrand , Ledoux , and others.

  7. Geometric median - Wikipedia

    en.wikipedia.org/wiki/Geometric_median

    For the 1-dimensional case, the geometric median coincides with the median.This is because the univariate median also minimizes the sum of distances from the points. (More precisely, if the points are p 1, ..., p n, in that order, the geometric median is the middle point (+) / if n is odd, but is not uniquely determined if n is even, when it can be any point in the line segment between the two ...

  8. Probability density function - Wikipedia

    en.wikipedia.org/wiki/Probability_density_function

    The probability mass function of a discrete random variable is the density with respect to the counting measure over the sample space (usually the set of integers, or some subset thereof). It is not possible to define a density with reference to an arbitrary measure (e.g. one can not choose the counting measure as a reference for a continuous ...

  9. Median (geometry) - Wikipedia

    en.wikipedia.org/wiki/Median_(geometry)

    In geometry, a median of a triangle is a line segment joining a vertex to the midpoint of the opposite side, thus bisecting that side. Every triangle has exactly three medians, one from each vertex, and they all intersect at the triangle's centroid .