<Tr> <Td> </Td> <Td> This article needs additional citations for verification . Please help improve this article by adding citations to reliable sources . Unsourced material may be challenged and removed . (April 2012) (Learn how and when to remove this template message) </Td> </Tr> <P> In probability and statistics, a probability mass function (pmf) is a function that gives the probability that a discrete random variable is exactly equal to some value . The probability mass function is often the primary means of defining a discrete probability distribution, and such functions exist for either scalar or multivariate random variables whose domain is discrete . </P> <P> A probability mass function differs from a probability density function (pdf) in that the latter is associated with continuous rather than discrete random variables; the values of the probability density function are not probabilities as such: a pdf must be integrated over an interval to yield a probability . </P> <P> The value of the random variable having the largest probability mass is called the mode . </P>

State the difference between pdf and pmf in probability distribution
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