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Poisson Approximation to the Binomial Distribution
The random variable X that is binomially distributed with
parameters p and n has the following
probability mass function:
The mean and variance of X are
E(X) = np
Var(X) = np(1-p)
If the value of n is large, and the value of p
is close to zero, then the binomial distribution with parameters p
and n can be approximated by a Poisson distribution with
parameter l = np. A random
variable X having this Poisson distribution will have a mean and
variance whose value is l = np,
i.e.,
E(X) = Var(X) = l = np
These values are the same as the mean and variance of a
binomial distribution with parameters p and n,
except that the values of the variances differ by a factor of (1-p).
However, if the value of p is close to zero, the value
of (1-p) is close to 1.
EX. A certain rare disease affects 1 out of every 10,000
persons in the US. The random variable X, the number of people in
a sample of 100,000 that are afflicted with this disease, is
binomially distributed with n = 100,000 and p =
0.0001. Since n is very large and p is close to zero, the Poisson
approximation to the binomial distribution should provide an
accurate estimate. Thus, the distribution of X approximates a
Poisson distribution with l = np
= (100000)(0.0001) = 10.
The probability that there are no more than 2 persons in the
sample of 100,000 that have the misfortune of contracting the
disease is
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