Uniform Density Function-ECO6416

Uniform Density Function-ECO6416 - Notice that any Uniform...

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Uniform Density Function The uniform density function gives the probability that observation will occur within a particular interval [a, b] when probability of occurrence within that interval is directly proportional to interval length. Its mean and variance are: μ = (a+b)/2, σ 2 = (b-a) 2 /12. Applications: Used to generate random numbers in sampling and Monte Carlo simulation. Comments: Special case of beta distribution. You might like to use Goodness-of-Fit Test for Uniform and performing some numerical experimentation for a deeper understanding of the concepts.
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Unformatted text preview: Notice that any Uniform distribution has uncountable number of modes having equal density value; therefore it is considered as a homogeneous population. Discrete Uniform Distribution: The discrete uniform distribution describes the distribution of n equally likely events (labeled with the integers from 1 to n), each with probability 1/n. If X is a discrete uniform random variable with parameter n, then the mean, and variance are as follows: E(X) = (n+1)/2, Var(X) = (n 2-1) /12...
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This note was uploaded on 10/04/2011 for the course ECO 6416 taught by Professor Staff during the Spring '08 term at University of Central Florida.

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