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  2. Grubbs's test - Wikipedia

    en.wikipedia.org/wiki/Grubbs's_test

    However, multiple iterations change the probabilities of detection, and the test should not be used for sample sizes of six or fewer since it frequently tags most of the points as outliers. [3] Grubbs's test is defined for the following hypotheses: H 0: There are no outliers in the data set H a: There is exactly one outlier in the data set

  3. Studentized residual - Wikipedia

    en.wikipedia.org/wiki/Studentized_residual

    This is an important technique in the detection of outliers. It is among several named in honor of William Sealey Gosset , who wrote under the pseudonym "Student" (e.g., Student's distribution ). Dividing a statistic by a sample standard deviation is called studentizing , in analogy with standardizing and normalizing .

  4. Dixon's Q test - Wikipedia

    en.wikipedia.org/wiki/Dixon's_Q_test

    In statistics, Dixon's Q test, or simply the Q test, is used for identification and rejection of outliers.This assumes normal distribution and per Robert Dean and Wilfrid Dixon, and others, this test should be used sparingly and never more than once in a data set.

  5. Cochran's C test - Wikipedia

    en.wikipedia.org/wiki/Cochran's_C_test

    Cochran's test, [1] named after William G. Cochran, is a one-sided upper limit variance outlier statistical test .The C test is used to decide if a single estimate of a variance (or a standard deviation) is significantly larger than a group of variances (or standard deviations) with which the single estimate is supposed to be comparable.

  6. Normal probability plot - Wikipedia

    en.wikipedia.org/wiki/Normal_probability_plot

    The normal probability plot is formed by plotting the sorted data vs. an approximation to the means or medians of the corresponding order statistics; see rankit.Some plot the data on the vertical axis; [1] others plot the data on the horizontal axis.

  7. Winsorizing - Wikipedia

    en.wikipedia.org/wiki/Winsorizing

    The distribution of many statistics can be heavily influenced by outliers, values that are 'way outside' the bulk of the data. A typical strategy to account for, without eliminating altogether, these outlier values is to 'reset' outliers to a specified percentile (or an upper and lower percentile) of the data. For example, a 90% winsorization ...

  8. Inside Israel’s daring raid that destroyed Iran-funded ...

    www.aol.com/news/inside-israel-daring-raid...

    Israel blew up an Iran sponsored Syrian missile factory after its elite commandos raided it last September. The missiles posed an existential threat to Israel amid its war against Tehran's proxies.

  9. SPSS - Wikipedia

    en.wikipedia.org/wiki/SPSS

    SPSS 27 - 2019, June [15] (and 27.0.1 in November, 2020 [16]) SPSS 28 - 2021, May [17] SPSS 29 - 2022, Sept [18] SPSS 30 - 2024, Sept [19] SPSS was released in its first version in 1968 as the Statistical Package for the Social Sciences (SPSS) after being developed by Norman H. Nie, Dale H. Bent, and C. Hadlai Hull.