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  2. Central tendency - Wikipedia

    en.wikipedia.org/wiki/Central_tendency

    Midrange the arithmetic mean of the maximum and minimum values of a data set. Midhinge the arithmetic mean of the first and third quartiles. Quasi-arithmetic mean A generalization of the generalized mean, specified by a continuous injective function. Trimean the weighted arithmetic mean of the median and two quartiles. Winsorized mean

  3. Mid-range - Wikipedia

    en.wikipedia.org/wiki/Mid-range

    For n = 1 or 2, the midrange and the mean are equal (and coincide with the median), and are most efficient for all distributions. For n = 3, the modified mean is the median, and instead the mean is the most efficient measure of central tendency for values of γ 2 from 2.0 to 6.0 as well as from −0.8 to 2.0.

  4. Median - Wikipedia

    en.wikipedia.org/wiki/Median

    The median of a symmetric unimodal distribution coincides with the mode. The median of a symmetric distribution which possesses a mean μ also takes the value μ. The median of a normal distribution with mean μ and variance σ 2 is μ. In fact, for a normal distribution, mean = median = mode.

  5. 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.

  6. Average - Wikipedia

    en.wikipedia.org/wiki/Average

    For example, the mean or average of the numbers 2, 3, 4, 7, and 9 (summing to 25) is 5. Depending on the context, the most representative statistic to be taken as the average might be another measure of central tendency, such as the mid-range, median, mode or geometric mean.

  7. Mean - Wikipedia

    en.wikipedia.org/wiki/Mean

    The mean of a set of observations is the arithmetic average of the values; however, for skewed distributions, the mean is not necessarily the same as the middle value (median), or the most likely value (mode). For example, mean income is typically skewed upwards by a small number of people with very large incomes, so that the majority have an ...

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