Inverse Distribution Function: The inverse distribution function or the quantile function can be defined when the CDF is increasing and continuous. The semi-closed interval in which the probability of ‘X’ lies is (a.b], where a x)=1−FX(x)įolded Cumulative Distribution: When the cumulative distributive function is plotted, and the plot resembles an ‘S’ shape it is known as FCD or mountain plot. The right-hand side of the cumulative distribution function formula represents the probability of a random variable ‘X’ which takes the value that is less than or equal to that of the x. What is a Cumulative Distribution Function?ĬDF of a random variable ‘X’ is a function which can be defined as, Understanding this is fundamental to understanding the Cumulative Distribution Function. What this means is that this variable explains the probable resulting values on an unexpected phenomenon. We mentioned that X is a random variable. In this case, the function holds that X will be of a lower value than x or will be valued the same as x. This function, also abbreviated as CDF, takes into account that a random variable valued at a real point, like X, is evaluated at x.
The Cumulative Distribution Function is a major part of both these sub-disciplines and it is used in a number of applications.
In Mathematics, Statistics and Probability play a very important role in helping to calculate data sufficiency.
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