In probability theory 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, given that the distribution is discrete.
A probability mass function differs from a probability density function (p.d.f.) in that the latter is associated with continuous rather than discrete random variables; the values of the latter are not probabilities as such: a p.d.f. must be integrated over an interval to yield a probability.
Read more about Probability Mass Function: Formal Definition, Examples
Famous quotes containing the words probability, mass and/or function:
“The source of Pyrrhonism comes from failing to distinguish between a demonstration, a proof and a probability. A demonstration supposes that the contradictory idea is impossible; a proof of fact is where all the reasons lead to belief, without there being any pretext for doubt; a probability is where the reasons for belief are stronger than those for doubting.”
—Andrew Michael Ramsay (16861743)
“Reduced to a miserable mass level, the level of a Hitler, German Romanticism broke out into hysterical barbarism.”
—Thomas Mann (18751955)
“... the function of art is to do more than tell it like it isits to imagine what is possible.”
—bell hooks (b. c. 1955)