In probability theory and statistics, the cumulative distribution function (CDF), or just distribution function, describes the probability that a real-valued random variable X with a given probability distribution will be found at a value less than or equal to x. Intuitively, it is the "area so far" function of the probability distribution. Cumulative distribution functions are also used to specify the distribution of multivariate random variables.
Read more about Cumulative Distribution Function: Definition, Properties, Examples, Multivariate Case, Use in Statistical Analysis
Famous quotes containing the words cumulative, distribution and/or function:
“But while ignorance can make you insensitive, familiarity can also numb. Entering the second half-century of an information age, our cumulative knowledge has changed the level of what appalls, what stuns, what shocks.”
—Anna Quindlen (b. 1952)
“The man who pretends that the distribution of income in this country reflects the distribution of ability or character is an ignoramus. The man who says that it could by any possible political device be made to do so is an unpractical visionary. But the man who says that it ought to do so is something worse than an ignoramous and more disastrous than a visionary: he is, in the profoundest Scriptural sense of the word, a fool.”
—George Bernard Shaw (1856–1950)
“Morality and its victim, the mother—what a terrible picture! Is there indeed anything more terrible, more criminal, than our glorified sacred function of motherhood?”
—Emma Goldman (1869–1940)