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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. Grubbs's test - Wikipedia

    en.wikipedia.org/wiki/Grubbs's_test

    This outlier is expunged from the dataset and the test is iterated until no outliers are detected. 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:

  4. Quartile - Wikipedia

    en.wikipedia.org/wiki/Quartile

    Outliers could also be evidence of a sample population that has a non-normal distribution or of a contaminated population data set. Consequently, as is the basic idea of descriptive statistics, when encountering an outlier, we have to explain this value by further analysis of the cause or origin of the outlier. In cases of extreme observations ...

  5. 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.

  6. Anomaly detection - Wikipedia

    en.wikipedia.org/wiki/Anomaly_detection

    In data analysis, anomaly detection (also referred to as outlier detection and sometimes as novelty detection) is generally understood to be the identification of rare items, events or observations which deviate significantly from the majority of the data and do not conform to a well defined notion of normal behavior. [1]

  7. The ‘girl math’ trend proves that women are still apologising ...

    www.aol.com/news/girl-math-trend-proves-women...

    The ‘girl math’ trend is the mental gymnastics women do to justify their purchases to themselves and to others. But Meredith Clark writes how the popular TikTok trend is perpetuating a ...

  8. Leverage (statistics) - Wikipedia

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

    The formula then divides by () to account for the fact that we remove the observation rather than adjusting its value, reflecting the fact that removal changes the distribution of covariates more when applied to high-leverage observations (i.e. with outlier covariate values). Similar formulas arise when applying general formulas for statistical ...

  9. ‘Girl math,’ the TikTok trend where young women justify their ...

    www.aol.com/finance/girl-math-tiktok-trend-where...

    Girl math is just the latest in a long line of “girl” trends, from this year’s “girl dinner” and “lazy girl jobs,” to last year’s “hot girl walks” and “hot girl summers ...