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  2. Outlier - Wikipedia

    en.wikipedia.org/wiki/Outlier

    The strength of this method lies in the fact that it takes into account a data set's standard deviation, average and provides a statistically determined rejection zone; thus providing an objective method to determine if a data point is an outlier. [citation needed] [24] How it works: First, a data set's average is determined. Next the absolute ...

  3. 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 ...

  4. Peirce's criterion - Wikipedia

    en.wikipedia.org/wiki/Peirce's_criterion

    First, the statistician may remove the suspected outliers from the data set and then use the arithmetic mean to estimate the location parameter. Second, the statistician may use a robust statistic, such as the median statistic. Peirce's criterion is a statistical procedure for eliminating outliers.

  5. 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]

  6. Anomaly detection - Wikipedia

    en.wikipedia.org/wiki/Anomaly_detection

    An outlier is an observation (or subset of observations) which appears to be inconsistent with the remainder of that set of data. [ 3 ] An anomaly is a point or collection of points that is relatively distant from other points in multi-dimensional space of features.

  7. 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:

  8. High-yield savings rates for February 12, 2025 - AOL

    www.aol.com/finance/savings-interest-rates-today...

    At the conclusion of its first rate-setting policy meeting of the year, on January 29, 2025, the Federal Reserve announced it was leaving the federal funds target interest rate at 4.25% to 4.50% ...

  9. Winsorizing - Wikipedia

    en.wikipedia.org/wiki/Winsorizing

    For instance, the 10% trimmed mean is the average of the 5th to 95th percentile of the data, while the 90% winsorized mean sets the bottom 5% to the 5th percentile, the top 5% to the 95th percentile, and then averages the data. Winsorizing thus does not change the total number of values in the data set, N.