The Central Limit Theorem

The Central Limit Theorem by itself makes the NormalDistribution the most important probability distribution. It statesthat any distribution can be approximated to some extent by thenormal distribution. Specifically, if a sample of size n is takenfrom a population with meanandvariancethenthe sample mean has the approximate distribution The mean and variance of some common distributions of given in thetable below.

Distribution

Parameters and Meaning of Parameters

Mean

Variance

Approximate Distribution of Sample Mean for Sampleof Size n

-mean

–standard deviation

Uniform,

andarethe minimum and maximum possible values of the random variable

Binomial,

isthe number of trials,isthe probability of success

Geometric,

isthe probability of success

Poisson,

isthe average number of events per time period

Example: For a sample of size 10 taken from a uniform distributionbetween the limitsandwhatis the probability that the average is less than 12?

This corresponds to a probability of 0.791.

Add comment

Security code
Refresh