Difference between revisions of "Cumulative distribution function"
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In [[probability theory]], a '''cumulative distribution function''' ''F(x)'' of a [[probability density function]] say ''f(x)'' is a real valued and continuous function whose value is the proportion of probability values of a variable which occur on the part of the real line up and including the value of that variable; i.e., | In [[probability theory]], a '''cumulative distribution function''' ''F(x)'' of a [[probability density function]] say ''f(x)'' is a real valued and continuous function whose value is the proportion of probability values of a variable which occur on the part of the real line up and including the value of that variable; i.e., | ||
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If the [[domain]] of the variable is [[finite]], then the upper limit in equation (2) above should be the upper bound of the variables [[domain of support]]. | If the [[domain]] of the variable is [[finite]], then the upper limit in equation (2) above should be the upper bound of the variables [[domain of support]]. | ||
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Latest revision as of 07:12, July 13, 2016
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In probability theory, a cumulative distribution function F(x) of a probability density function say f(x) is a real valued and continuous function whose value is the proportion of probability values of a variable which occur on the part of the real line up and including the value of that variable; i.e.,
Considering this definition in light of the Fundamental Theorem of Calculus yields:
Due to the properties of the probability density function f(x), the cumulative distribution function F(x) will have the following properties:
(1) inside its domain of support.
(2) , i.e., finitely convergent (to unity by convention).
(3) for a<b, i.e., is non-decreasing
If the domain of the variable is finite, then the upper limit in equation (2) above should be the upper bound of the variables domain of support.
