Deriving a Probability Generating Function for Independent Poisson Variables

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Discussion Overview

The discussion revolves around deriving the Probability Generating Function (PGF) for the sum of two independent Poisson random variables, ##X## and ##Y##. Participants explore the properties of the PGF for Poisson distributions and clarify the distinction between homework and test preparation contexts.

Discussion Character

  • Technical explanation
  • Homework-related
  • Meta-discussion

Main Points Raised

  • One participant asks how to derive the PGF for the sum of two independent Poisson variables, suggesting that it may be ##G(t) = e^{-(\lambda_X + \lambda_Y)(1-t)}##.
  • Another participant references the Encyclopedia of Mathematics, indicating that the initial suggestion is correct according to its description of Poisson distribution characteristics.
  • There is a discussion about whether the original query constitutes a homework problem or test preparation, with one participant asserting that they are preparing for a test.
  • Multiple participants express the view that the forum rules categorize the inquiry as a homework problem, leading to a debate about the appropriateness of the post's context.
  • Suggestions are made about where to post similar questions, including a recommendation to use the Calculus forum and a link to an external resource on Poisson distributions.

Areas of Agreement / Disagreement

Participants do not reach a consensus on whether the original post is a homework question or a test preparation inquiry, leading to ongoing debate about the classification of the discussion.

Contextual Notes

The discussion reflects differing interpretations of forum rules regarding homework versus test preparation, which may affect how participants engage with the topic.

user366312
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Can anyone kindly tell me how I can derive a Probability Generating Function of Poisson Distribution for ##X+Y## where ##X## and ##Y## are independent?

I know that PGF for a single variate Poisson Distribution is: ##G(t) = e^{-\lambda (1-t)}##.

Then how can I derive a PGF for the same?

Is it: ##G(t) = e^{-(\lambda_X + \lambda_Y)(1-t)}## ?

Why or why not?
 
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Encyclopedia of Mathematics describes Poisson distribution characteristics according to which you are right.
 
user366312 said:
I am not doing homework. I am preparing for a test. I believe there are differences between these two.
Forum rules do not view it that way
 
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StoneTemplePython said:
Forum rules do not view it that way

Okay. I accept.
 
StoneTemplePython said:
Forum rules do not view it that way

Where can/should I post these kinds of problems?
 
user366312 said:
I am not doing homework. I am preparing for a test. I believe there are differences between these two.
user366312 said:
Okay. I accept.
Thank you. You will get great help in the schoolwork forums on your questions, as long as you show your efforts. :smile:
 

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