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  2. 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.

  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. 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.

  5. 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.

  6. 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

  7. Student's t-distribution - Wikipedia

    en.wikipedia.org/wiki/Student's_t-distribution

    The function A(t | ν) is the integral ... The classical approach was to identify outliers (e.g., using Grubbs's ... for example, the chemical properties of barley ...

  8. Chemical formula - Wikipedia

    en.wikipedia.org/wiki/Chemical_formula

    An example is the condensed molecular/chemical formula for ethanol, which is CH 3 −CH 2 −OH or CH 3 CH 2 OH. However, even a condensed chemical formula is necessarily limited in its ability to show complex bonding relationships between atoms, especially atoms that have bonds to four or more different substituents.

  9. List of unsolved problems in chemistry - Wikipedia

    en.wikipedia.org/wiki/List_of_unsolved_problems...

    This article needs attention from an expert in chemistry. The specific problem is: Incomplete list. WikiProject Chemistry may be able to help recruit an expert.