cumulative distribution function

(1.1 hours to learn)


The cumulative distribution function (CDF) of a random variable X is the function F, where F(a) is the probability that X <= a. CDFs are a convenient representation because they apply to both discrete and continuous random variables, and they can simplify many calculations.


This concept has the prerequisites:


  • Know the definition and basic properties of the CDF
  • Be able to use the CDF of a distribution to:
    • determine the probability that a random variable lies in a given range
    • recover the probability mass function or the probability density function

Core resources (read/watch one of the following)


Supplemental resources (the following are optional, but you may find them useful)


Sets, Counting, and Probability
Online lectures on basic probability theory.
Location: Lecture "Random variables"


See also

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