What is the Expected Value of X with Poisson Distribution?

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In summary, the conversation discussed finding the expected value of x using Poisson distribution and the use of Taylor series expansion to simplify the calculation. The main point of confusion was the equality between the sum and e^x, which is a result of the Taylor series expansion of e^x. The conversation also expressed frustration with these types of sums and how they can be challenging to remember.
  • #1
ArcanaNoir
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Homework Statement



Finding the expected value of x, with poisson distribution. I don't follow the sum. It goes like this:

[tex] E(x)= \sum_{x=0}^{\infty} \frac{xe^{-\lambda}\lambda^x}{x!} [/tex]
[tex] = e^{-\lambda} \sum_{x=0}^{\infty} \frac{x\lambda^x}{x(x-1)!} [/tex]
[tex] = \lambda e^{-\lambda} \sum_{x=1}^{\infty} \frac{\lambda^{x-1}}{(x-1)!} [/tex]
[tex] = \lambda e^{-\lambda} \sum_{k=0}^{\infty} \frac{\lambda^{k}}{k!} [/tex]
[tex] = \lambda e^{-\lambda}e^{\lambda} = \lambda [/tex]


So basically the part I don't get is why they say
[tex] \sum_{k=0}^{\infty} \frac{\lambda^{k}}{k!} = e^{\lambda} [/tex]
 
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  • #2
That is just the Taylor series expansion of [itex]e^x[/itex]. Remember that

[tex]f(x)=\sum_{k=0}^{+\infty}{\frac{f^{(k)}(0)}{k!}x^k}[/tex]

So if [itex]f(x)=e^x[/itex], then

[tex]e^x=\sum_{k=0}^{+\infty}{\frac{x^k}{k!}}[/tex]
 
  • #3
Thanks micro. This chapter is going to be the death of me. All kinds of crazy sums that end up with specific values that I'm supposed to remember from two weeks in calc II. Doomed! I hate sums.
 
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