Bimodal
This article covers meaning & overview of Bimodal from statistical perspective.
What is Bimodal?
A continuous probability distribution with two different modes is called a bimodal distribution. Simply put a dataset where two data values have the same highest frequency is called a bimodal dataset. A distribution can have even more than two modes & can be referred to as a multimodal distribution. In the probability density functions, these appear as distinct peaks.
If the modes are unequal, the larger is referred to as the major mode while the smaller is the minor mode. A bimodal distribution is mostly the resultant of two distinct unimodal distributions but the mixture of two different unimodal distribution is not necessarily bimodal. The unique characteristic of a bimodal distribution is that mostly in such distribution the mean is used as a robust sample estimator and not the median. An example of a bimodal distribution is the combination of the distribution of the heights of men and women, although the difference between the mean heights may be less significant than their standard deviation. Important bimodal distributions cover distributions like the arcsine distribution, the beta distribution, the U-quadratic distribution etc.
A data set of values 1,2,2,2,3,3,4,5,5,6,6,6,7,7 is bimodal since both 2 & 6 show up the highest number of times i.e. twice
Hence, this concludes the definition of Bimodal along with its overview.
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