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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. 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.

  5. 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]

  6. Quizlet - Wikipedia

    en.wikipedia.org/wiki/Quizlet

    In November 2022, Quizlet announced a new CEO, Lex Bayer, the former CEO of Starship Technologies. [23] In March 2023, Quizlet started to incorporate AI features with the release "Q-Chat", a virtual AI tutor powered by OpenAI's ChatGPT API. [24] [25] [26] Quizlet launched four additional AI powered features in August 2023 to assist with student ...

  7. Robust statistics - Wikipedia

    en.wikipedia.org/wiki/Robust_statistics

    First, an outlier detection method that relies on a non-robust initial fit can suffer from the effect of masking, that is, a group of outliers can mask each other and escape detection. [17] Second, if a high breakdown initial fit is used for outlier detection, the follow-up analysis might inherit some of the inefficiencies of the initial estimator.

  8. J. Ann Selzer, pollster who predicted Kamala Harris would win ...

    www.aol.com/news/pollster-predicted-kamla-harris...

    J. Ann Selzer's once-respected poll showed that Kamala Harris was leading in Iowa — only for Trump to win the state by more than 13 percentage points on Election Day.

  9. Influential observation - Wikipedia

    en.wikipedia.org/wiki/Influential_observation

    An outlier may be defined as a data point that differs markedly from other observations. [6] [7] A high-leverage point are observations made at extreme values of independent variables. [8] Both types of atypical observations will force the regression line to be close to the point. [2]