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  2. Fan chart (time series) - Wikipedia

    en.wikipedia.org/wiki/Fan_chart_(time_series)

    The split normal density is completely characterized by three parameters, the mode, variance and skewness. Therefore, the fan chart ranges depend on these parameters only. [4] [5] [6] and [8] In a central bank that employs inflation targeting, the three moments of the inflation forecast distribution are determined as follows: The mode.

  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 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 ...

  5. Range mode query - Wikipedia

    en.wikipedia.org/wiki/Range_mode_query

    The mode of the block can be retrieved from . By Theorem 1, the mode can be either an element of the prefix (indices of [:] before the start of the span), an element of the suffix (indices of [:] after the end of the span), or .

  6. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    [4] [5] Their importance is partly due to the central limit theorem. It states that, under some conditions, the average of many samples (observations) of a random variable with finite mean and variance is itself a random variable—whose distribution converges to a normal distribution as the number of samples increases.

  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)

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  9. 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.

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