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Poisson Distribution Part I
The normal distribution is symmetric and is used to
approximate the binomial distribution when p = q = 1/2.
When p is very small, then the resulting distribution
is not symmetric as the number of trials becomes large.
When n, the number of trials is large and p is very
small we approximate the binomial distribution with
the Poisson distribution.
The Poisson distribution is used when the probability
of success is very small. The probability of a mutation
is very small. The probability of a double-cross over
is small. Haldane and Kosambi used the Poisson distribution
to adjust the observed number of crossover events to
the map distance. Map distance is the distance between
loci on a chromosome and is not the same as the recombination
proportion. A characteristic of the Poisson distribution
is that the population mean and variance are equal.
We will use the Poisson distribution later when we discuss
mapping functions.
Let m = the mean number of successful events. The probability
of x successful events is given by the formula.
| e-m |
( |
1, |
m,
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m2, |
m3, |
m4, |
...mi |
) |
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2!, |
3!, |
4!, |
i! |
Copyright
2000©, Ted Helms |
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