Let X, Y be independent and identically distributed random variables, each having Poisson distribution with rate parameter λ. Find the probability generating function of W = X + Y and hence the mean and variance of W
"X" has a Poisson distribution. It means that "X" takes values from the set of nonnegative integers "0,1,2,..." and "P(X=k)=\\frac{\\lambda^ke^{-\\lambda}}{k!}", where "k=0,1,2,...". For "Y" we have: "P(Y=n)=\\frac{\\lambda^ne^{-\\lambda}}{n!}", "n=0,1,2,...". A random variable "W=X+Y" has a Poisson distribution with parameter "2\\lambda". It is a well-known fact. It can be also checked directly: "P(W=n)=P(X+Y=n)=\\sum_{k=0}^nP(X=k,Y=n-k)=\\sum_{k=0}^n\\frac{\\lambda^ke^{-\\lambda}}{k!}\\frac{\\lambda^{n-k}e^{-\\lambda}}{(n-k)!}=\\sum_{k=0}^n\\frac{\\lambda^ne^{-2\\lambda}}{k!(n-k)!}=\\frac{e^{-2\\lambda}}{n!}\\sum_{k=0}^n\\frac{n!\\lambda^n}{k!(n-k)!}=\\frac{(2\\lambda)^n}{n!}e^{-2\\lambda}"
We used a binomial formula. Remind that the probability generating function for "W" has the form:
"G(z)=E[z^W]=\\sum_{x=0}^{+\\infty}p(x)z^x=\\sum_{x=0}^{+\\infty}\\frac{(2\\lambda)^x}{x!}e^{-2\\lambda}z^x=e^{-2\\lambda}\\sum_{x=0}^{+\\infty}\\frac{(2\\lambda z)^x}{x!}=e^{2\\lambda(z-1)}"
We used a Taylor series expansion for "e^{2\\lambda z}". The latter is a known formula. Substitute "z=e^t". We receive: "M(t)=E[e^{tW}]=e^{2\\lambda(e^t-1)}". This is a moment-generating function. Using the known formulae, we have: "E[W]=M'(0)=(2\\lambda e^te^{2\\lambda(e^t-1)})|_{t=0}=2\\lambda".
"E[W^2]=M''(0)=(2\\lambda e^te^{2\\lambda(e^t-1)}+4\\lambda^2 e^{2t}e^{2\\lambda(e^t-1)})|_{t=0}=2\\lambda+4\\lambda^2".
"Var[W]=E[W^2]-(E[W])^2=2\\lambda+4\\lambda^2-4\\lambda^2=2\\lambda"
Answer: The probability generating function of "W" is: "G(z)=E[z^W]=e^{2\\lambda(z-1)}". The mean is: "E[W]=2\\lambda", "Var[W]=2\\lambda".
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