Probability mass function: Difference between revisions

Revision as of 22:13, 16 February 2007

Revision as of 22:14, 16 February 2007

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Suppose that ''X'' is the outcome of a single coin toss, assigning 0 to tails and 1 to heads. The probability that ''X'' = ''x'' is 0.5 on the state space {0, 1} (this is a [[Bernoulli distribution|Bernoulli random variable]]), and hence the probability mass function is

:<math>f_X(x) = \begin{cases}\frac{1}{2}, &x \in \{0, 1\},\\0, &x \in \mathbb{R}\backslash\{0, 1\}.\end{cases}</math>

Probability mass functions may also be defined for any discrete random variable, including [[constant random variable|constant]], [[Binomial distribution|binomial]] (including [[Bernoulli distribution|Bernoulli]]), [[negative binomial distribution|negative binomial]], [[Poisson distribution|Poisson]], [[geometric distribution|geometric]] and [[hypergeometric distribution|hypergeometric]] random variables.

[[Category:Probability theory]]