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Mathematical Methods for Physicists: A concise introduction - Site Map

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SPECIAL PROBABILITY DISTRIBUTIONS<br />

and the standard deviation ;<br />

ˆ<br />

p npq : …14:24†<br />

Two di€erent limits of the binomial distribution <strong>for</strong> large n are of practical<br />

importance: (1) n !1and p ! 0 in such a way that the product np ˆ remains<br />

constant; (2) both n and pn are large. The ®rst case will result a new distribution,<br />

the Poisson distribution, and the second cases gives us the Gaussian (or Laplace)<br />

distribution.<br />

The Poisson distribution<br />

Now np ˆ ; so p ˆ =n. The binomial distribution (14.16) then becomes<br />

<br />

n! m <br />

f …m† ˆP…X ˆ m† ˆ<br />

1 nm<br />

m!…n m†! n n<br />

<br />

n…n 1†…n 2†…n m ‡ 1†<br />

ˆ<br />

m!n m m 1 nm<br />

n<br />

<br />

ˆ 1 1 <br />

1 2 <br />

1 m 1 <br />

m <br />

1 nm<br />

: …14:25†<br />

n n<br />

n m! n<br />

Now as n !1,<br />

<br />

1 1 n<br />

<br />

1 2 <br />

n<br />

<br />

1 m 1 <br />

! 1;<br />

n<br />

while<br />

<br />

1 nmˆ 1 n <br />

1 m<br />

<br />

! e <br />

… 1†<br />

ˆ e ;<br />

n<br />

n n<br />

where we have made use of the result<br />

<br />

lim 1 ‡ nˆ e :<br />

n!1 n<br />

It follows that Eq. (14.25) becomes<br />

f …m† ˆP…X ˆ m† ˆm e <br />

: …14:26†<br />

m!<br />

This is known as the Poisson distribution. Note that P 1<br />

mˆ0<br />

P…X ˆ m† ˆ1; as it<br />

should.<br />

495

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