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  2. Fan chart (statistics) - Wikipedia

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

    A dispersion fan diagram (left) in comparison with a box plot. A fan chart is made of a group of dispersion fan diagrams, which may be positioned according to two categorising dimensions. A dispersion fan diagram is a circular diagram which reports the same information about a dispersion as a box plot: namely median, quartiles, and two extreme ...

  3. Quantile - Wikipedia

    en.wikipedia.org/wiki/Quantile

    Hyndman and Fan compiled a taxonomy of nine algorithms [2] used by various software packages. All methods compute Q p , the estimate for the p -quantile (the k -th q -quantile, where p = k / q ) from a sample of size N by computing a real valued index h .

  4. Mean absolute scaled error - Wikipedia

    en.wikipedia.org/wiki/Mean_absolute_scaled_error

    It was proposed in 2005 by statistician Rob J. Hyndman and Professor of Decision Sciences Anne B. Koehler, who described it as a "generally applicable measurement of forecast accuracy without the problems seen in the other measurements."

  5. Percentile - Wikipedia

    en.wikipedia.org/wiki/Percentile

    The 25th percentile is also known as the first quartile (Q 1), the 50th percentile as the median or second quartile (Q 2), and the 75th percentile as the third quartile (Q 3). For example, the 50th percentile (median) is the score below (or at or below , depending on the definition) which 50% of the scores in the distribution are found.

  6. Rob J. Hyndman - Wikipedia

    en.wikipedia.org/wiki/Rob_J._Hyndman

    Robin John Hyndman (born 2 May 1967 [citation needed]) is an Australian statistician known for his work on forecasting and time series. He is a Professor of Statistics at Monash University [ 1 ] and was Editor-in-Chief of the International Journal of Forecasting from 2005–2018. [ 2 ]

  7. Percentile rank - Wikipedia

    en.wikipedia.org/wiki/Percentile_rank

    The figure illustrates the percentile rank computation and shows how the 0.5 × F term in the formula ensures that the percentile rank reflects a percentage of scores less than the specified score. For example, for the 10 scores shown in the figure, 60% of them are below a score of 4 (five less than 4 and half of the two equal to 4) and 95% are ...

  8. Quantile function - Wikipedia

    en.wikipedia.org/wiki/Quantile_function

    The probit is the quantile function of the normal distribution.. In probability and statistics, the quantile function outputs the value of a random variable such that its probability is less than or equal to an input probability value.

  9. 97.5th percentile point - Wikipedia

    en.wikipedia.org/wiki/97.5th_percentile_point

    In probability and statistics, the 97.5th percentile point of the standard normal distribution is a number commonly used for statistical calculations. The approximate value of this number is 1.96 , meaning that 95% of the area under a normal curve lies within approximately 1.96 standard deviations of the mean .