Advanced High-School Mathematics

(Tina Meador) #1

SECTION 6.1 Discrete Random Variables 339


We expect that the mean of the Poisson random variable isμ; how-
ever, a direct proof is possible as soon as we remember the Maclaurin
series expansion forex(see Exercise 1 on page 302). We have that


E(X) =

∑∞
k=0

kP(X=k)

=

∑∞
k=0

k

e−μμk
k!

=

∑∞
k=0

e−μμk+1
k!

= μe−μ

∑∞
k=0

μk
k!

=μe−μeμ=μ,

as expected.


Similarly,

Var(X) = E(X^2 )−μ^2
=

∑∞
k=0

k^2 P(X=k)−μ^2

=

∑∞
k=0

k^2

e−μμk
k!

−μ^2

= e−μ

∑∞
k=0

k
μk+1
k!

−μ^2

= μe−μ

∑∞
k=0

(k+ 1)

μk
k!

−μ^2

= μe−μ

∑∞
k=0

k

μk
k!

+μe−μ

∑∞
k=0

μk
k!

−μ^2

= μ^2 e−μ

∑∞
k=0

μk
k!
+μ−μ^2

= μ^2 +μ−μ^2 =μ.

That is to say, Var(X) =μ=E(X).

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