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).