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  2. Outlier - Wikipedia

    en.wikipedia.org/wiki/Outlier

    The modified Thompson Tau test is used to find one outlier at a time (largest value of δ is removed if it is an outlier). Meaning, if a data point is found to be an outlier, it is removed from the data set and the test is applied again with a new average and rejection region. This process is continued until no outliers remain in a data set.

  3. Interquartile range - Wikipedia

    en.wikipedia.org/wiki/Interquartile_range

    Box-and-whisker plot with four mild outliers and one extreme outlier. In this chart, outliers are defined as mild above Q3 + 1.5 IQR and extreme above Q3 + 3 IQR. The interquartile range is often used to find outliers in data. Outliers here are defined as observations that fall below Q1 − 1.5 IQR or above Q3 + 1.5 IQR.

  4. Peirce's criterion - Wikipedia

    en.wikipedia.org/wiki/Peirce's_criterion

    In data sets containing real-numbered measurements, the suspected outliers are the measured values that appear to lie outside the cluster of most of the other data values. . The outliers would greatly change the estimate of location if the arithmetic average were to be used as a summary statistic of locati

  5. Dixon's Q test - Wikipedia

    en.wikipedia.org/wiki/Dixon's_Q_test

    However, at 95% confidence, Q = 0.455 < 0.466 = Q table 0.167 is not considered an outlier. McBane [1] notes: Dixon provided related tests intended to search for more than one outlier, but they are much less frequently used than the r 10 or Q version that is intended to eliminate a single outlier.

  6. Chauvenet's criterion - Wikipedia

    en.wikipedia.org/wiki/Chauvenet's_criterion

    The idea behind Chauvenet's criterion finds a probability band that reasonably contains all n samples of a data set, centred on the mean of a normal distribution.By doing this, any data point from the n samples that lies outside this probability band can be considered an outlier, removed from the data set, and a new mean and standard deviation based on the remaining values and new sample size ...

  7. Five-number summary - Wikipedia

    en.wikipedia.org/wiki/Five-number_summary

    These quartiles are used to calculate the interquartile range, which helps to describe the spread of the data, and determine whether or not any data points are outliers. In order for these statistics to exist, the observations must be from a univariate variable that can be measured on an ordinal, interval or ratio scale .

  8. 8 Big Outliers That Should Revert to the Mean - AOL

    www.aol.com/news/2013-09-11-8-big-outliers-that...

    The article 8 Big Outliers That Should Revert to the Mean originally appeared on Fool.com. Fool contributor Morgan Housel has no position in any stocks mentioned. The Motley Fool recommends Ford ...

  9. 68–95–99.7 rule - Wikipedia

    en.wikipedia.org/wiki/68–95–99.7_rule

    For example, Φ(2) ≈ 0.9772, or ... To use as a test for outliers or a normality test, one computes the size of deviations in terms of standard deviations, and ...