Question

व्हाट इज द फार्मूला टू फाइंड मोड​

Answer 1

Answer:

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Step-by-step explanation:

The answers given so far are correct for data and (most) discrete probability densities (aka "mass distributions"); for continuous probability densities, such as the normal, gamma, chi-square, etc., a mode is the location of a (local) maximum of the probability density (of which there may be more than one, but this is very uncommon). As such, there isn't a "formula" per se—since each probability distribution is uniquely defined by its density function, no general formula is possible—but rather an algorithm for finding the mode(s), namely the standard algorithm from Calculus for finding local maxima of functions. To wit, take the derivative of the density function (given, say, as a function of x ), set it equal to zero, and solve for x : for "unimodal" distributions (which are the overwhelming majority of what's used in practice) you will get a unique value, and due to the nature of pdf's, it is guaranteed to be the location of the maximum, and thus the mode of the continuous probability distribution. Shortcuts: for symmetric distributions, e.g., normal, Students' t , etc., mode=median=mean (when this last is well defined); for common asymmetric distributions, e.g., chi-square, Snedecor's F , etc., a formula for the mode in terms of the distribution's parameters should be "locatable," in an intermediate/advanced statistics text and/or on-line (e.g., Wikipedia gives the formula for the mode of the F distribution under its article's "Quick Facts,"); for the continuous uniform distribution, the mode is undefined, because all possible values are equally likely and thus the pdf is "flat."

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Answer 2

Step-by-step explanation:

The mode is the most common number in a set. For example, the mode in this set of numbers is 21:

(21, 21, 21, 23, 24, 26, 26, 28, 29, 30, 31, 33)

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