The Discrete Uniform Distribution

Introduces the discrete uniform distribution: its probability mass function, computation of event probabilities, and formulas for the mean and variance, both for the standard form on {1, 2, ..., n} and the general form on {a, a+1, ..., b}.

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The Discrete Uniform Distribution

A discrete random variable XX follows a discrete uniform distribution on the finite set {x1,x2,,xn}\{x_1, x_2, \ldots, x_n\} if each of the nn values is equally likely. Its probability mass function is

P(X=xi)=1nfor i=1,2,,n.P(X = x_i) = \dfrac{1}{n} \quad \text{for } i = 1, 2, \ldots, n.

The most common case is XUniform{1,2,,n},X \sim \text{Uniform}\{1, 2, \ldots, n\}, where

P(X=k)=1nfor k=1,2,,n.P(X = k) = \dfrac{1}{n} \quad \text{for } k = 1, 2, \ldots, n.

For example, rolling a fair six-sided die gives XUniform{1,2,3,4,5,6},X \sim \text{Uniform}\{1, 2, 3, 4, 5, 6\}, so

P(X=4)=16.P(X = 4) = \dfrac{1}{6}.

To compute the probability of an event A,A, count the number of values in AA and divide by n:n{:}

P(XA)=An.P(X \in A) = \dfrac{|A|}{n}.

For the fair die, P(X5)={5,6}6=26=13.P(X \geq 5) = \dfrac{|\{5,6\}|}{6} = \dfrac{2}{6} = \dfrac{1}{3}.

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