Central Limit Theorem
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The Central Limit Theorem identifies the distribution of the sample mean and is arguably the most important theorem in probability theory.
Let
be a random variable, and let
be a random sample for
, such that each
has a distribution identical to that of
itself. Let
be the sample mean; in other words, let
be equal to
. Because each
is a random variable,
is also a random variable. The Central Limit Theorem observes several important facts about the distribution of
:
- The distribution of
is approximately normal, even when the underlying distribution
is not.
- The expected value of the
is equal to the expected value of
.
- As the sample size
increases, the variance of
approaches zero.
