For the a Poisson random variable x generating function G(t)= exp^lambda(t-1) show that the expected value E(x) and variance (x) are given by lambda and lambda respectively.
G(t)=eλ(et−1)G(t)=e^{\lambda(e^t-1)}G(t)=eλ(et−1)
E(x)=G′(0)E(x)=G'(0)E(x)=G′(0)
G′(t)=λeteλ(et−1)=λeλt(et−1)G'(t)=\lambda e^te^{\lambda(e^t-1)}=\lambda e^{\lambda t(e^t-1)}G′(t)=λeteλ(et−1)=λeλt(et−1)
G′(0)==λeλ0(et−1)=λG'(0)==\lambda e^{\lambda 0(e^t-1)}=\lambdaG′(0)==λeλ0(et−1)=λ
var(x)=E(x2)−[E(x)]2var(x)=E(x^2)-[E(x)]^2var(x)=E(x2)−[E(x)]2
E(X2)=G′′(0)E(X^2)=G''(0)E(X2)=G′′(0)
G′′(t)=λeλet+t−λ(λet+1)G''(t)=\lambda e^{\lambda e^t+t-\lambda}(\lambda e^t+1)G′′(t)=λeλet+t−λ(λet+1)
G′′(0)=λeλe0+0−λ(λe0+1)=λ(λ+1)=λ2+λG''(0)=\lambda e^{\lambda e^0+0-\lambda}(\lambda e^0+1)=\lambda(\lambda+1)=\lambda^2+\lambdaG′′(0)=λeλe0+0−λ(λe0+1)=λ(λ+1)=λ2+λ
From the first part, E(x)=λE(x)=\lambdaE(x)=λ . Thus;
var(x)=E(x2)−[E(x)]2=λ2+λ−λ2=λvar(x)=E(x^2)-[E(x)]^2=\lambda^2+\lambda-\lambda^2=\lambdavar(x)=E(x2)−[E(x)]2=λ2+λ−λ2=λ
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