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  2. Skewness - Wikipedia

    en.wikipedia.org/wiki/Skewness

    For example, in the distribution of adult residents across US households, the skew is to the right. However, since the majority of cases is less than or equal to the mode, which is also the median, the mean sits in the heavier left tail. As a result, the rule of thumb that the mean is right of the median under right skew failed. [2]

  3. 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.

  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. Nonparametric skew - Wikipedia

    en.wikipedia.org/wiki/Nonparametric_skew

    For an arbitrary distribution the mode, median and mean may appear in any order. [31] [32] [33] Analyses have been made of some of the relationships between the mean, median, mode and standard deviation. [34] and these relationships place some restrictions on the sign and magnitude of the nonparametric skew.

  6. 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.

  7. Glossary of probability and statistics - Wikipedia

    en.wikipedia.org/wiki/Glossary_of_probability...

    Perfectly symmetrical distributions always have zero skewness, though zero skewness does not necessarily imply a symmetrical distribution. The mean and median of a skewed distribution (left and right) may differ substantially from those of a symmetrical distribution (center) with zero skewness. spaghetti plot spectrum bias standard deviation

  8. Central tendency - Wikipedia

    en.wikipedia.org/wiki/Central_tendency

    the weighted arithmetic mean of the median and two quartiles. Winsorized mean an arithmetic mean in which extreme values are replaced by values closer to the median. Any of the above may be applied to each dimension of multi-dimensional data, but the results may not be invariant to rotations of the multi-dimensional space. Geometric median

  9. 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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