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Then the probability mass function f(X=x) = P () The table could be created on the basis of a random variable and possible outcomes.Say, a random variable X is a real-valued function whose domain is the sample space of a random experiment. X is the random variable of the number of heads obtained.
To be explicit, this is an example of a discrete univariate probability distribution with finite support.
The probability distribution gives the possibility of each outcome of a random experiment or events.
It provides the probabilities of different possible occurrence.
Probability mass function is basically defined for scalar or multivariate random variables whose domain is variant or discrete.
Let us discuss its formula: Suppose a random variable X and sample space S is defined as; X : S → A And A ∈ R, where R is a discrete random variable.