MHB MGF relating to random sum of random variables

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The discussion revolves around understanding the moment generating function (MGF) in the context of a random sum of random variables, specifically relating to customer arrivals during a service time that follows a Gamma distribution. The MGF of the random variable N, representing the number of customers, is expressed as the expectation of an exponential function of N. The challenge lies in calculating the probability $\mathbb{P}(N=n)$, which represents the likelihood of n customers arriving during the service time T. The user seeks guidance on how to proceed with the problem, particularly in incorporating the random nature of T into the MGF calculation. Clarifying these concepts will aid in solving the question effectively.
nedflanders
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Hi all

I am doing this question right now and I don't even know how to start it up.
I know that it's in relation to a sum of a random number of random variables, but I don't know how to continue on from that.

I've read my textbook and it states some definition for an MGF which is:
$M_{y}(t) = \sum_{n=0}^{\infty} M_{X}(t)^n p_{N}(n)$ but it doesn't derive it, however, I think it relates to this question?

The question is as follows:
YNJovOc.png
Thanks for the help
 
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The random variable $N$ is defined as the number of customers arriving during the service time $T$ of a customer. If $t$ was a constant you could just apply the MGF of the Poisson distribution. But now $T$ is a random variable which has a Gamma distribution so we have to take that into account. The MGF of $N$ is defined as
$$\mbox{MGF}_{N}(k) = \mathbb{E}[e^{kN}] = \sum_{n=0}^{\infty} e^{kn} \mathbb{P}(N=n)$$

The only thing we have to do now is to calculate $\mathbb{P}(N=n)$ which is the probability that $n$ customers will arive at a service station during the service time $T$.

Any thoughts?
 
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