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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.
The Beta distribution on [0,1], a family of two-parameter distributions with one mode, of which the uniform distribution is a special case, and which is useful in estimating success probabilities. The four-parameter Beta distribution, a straight-forward generalization of the Beta distribution to arbitrary bounded intervals [,].
Comparison of mean, median and mode of two log-normal distributions with different skewness. The mode is the point of global maximum of the probability density function. In particular, by solving the equation () ′ =, we get that:
In statistics, a central tendency ... Correspondingly, the mode is not unique – for example, in a uniform distribution any point is the mode. Clustering
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]
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 ...
Flying is the safest mode of transportation." And while there are copious amounts of data and statistics to back this up, once I hear an unfamiliar noise or we start going through unexpected ...
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