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  2. Mode (statistics) - Wikipedia

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

    The mode of a sample is the element that occurs most often in the collection. For example, the mode of the sample [1, 3, 6, 6, 6, 6, 7, 7, 12, 12, 17] is 6. Given the list of data [1, 1, 2, 4, 4] its mode is not unique. A dataset, in such a case, is said to be bimodal, while a set with more than two modes may be described as multimodal.

  3. Central tendency - Wikipedia

    en.wikipedia.org/wiki/Central_tendency

    For example, given binary data, say heads or tails, if a data set consists of 2 heads and 1 tails, then the mode is "heads", but the empirical measure is 2/3 heads, 1/3 tails, which minimizes the cross-entropy (total surprisal) from the data set.

  4. Mean - Wikipedia

    en.wikipedia.org/wiki/Mean

    The mode income is the most likely income and favors the larger number of people with lower incomes. While the median and mode are often more intuitive measures for such skewed data, many skewed distributions are in fact best described by their mean, including the exponential and Poisson distributions.

  5. Statistic - Wikipedia

    en.wikipedia.org/wiki/Statistic

    There are a variety of functions that are used to calculate statistics. Some include: Sample mean, sample median, and sample mode; Sample variance and sample standard deviation; Sample quantiles besides the median, e.g., quartiles and percentiles; Test statistics, such as t-statistic, chi-squared statistic, f statistic

  6. Talk:Mode (statistics) - Wikipedia

    en.wikipedia.org/wiki/Talk:Mode_(statistics)

    The article gives the example of a data sample [1, 1, 2, 4, 4] and states: "the mode is not unique". That is about all that can be said about it. Depending on your needs, predilections, and local customs, you can pick your choice between: (a) for this sample the mode is undefined; (b) this sample actually has two modes: 1 and 4; and (c) the ...

  7. Statistics - Wikipedia

    en.wikipedia.org/wiki/Statistics

    Again, descriptive statistics can be used to summarize the sample data. However, drawing the sample contains an element of randomness; hence, the numerical descriptors from the sample are also prone to uncertainty. To draw meaningful conclusions about the entire population, inferential statistics are needed. It uses patterns in the sample data ...

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  9. Unimodality - Wikipedia

    en.wikipedia.org/wiki/Unimodality

    The term "mode" in this context refers to any peak of the distribution, not just to the strict definition of mode which is usual in statistics. If there is a single mode, the distribution function is called "unimodal". If it has more modes it is "bimodal" (2), "trimodal" (3), etc., or in general, "multimodal". [2]