Problem of the Week #124 - August 11th, 2014

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SUMMARY

The problem discussed involves calculating the probability that a Geometric random variable \(Y\) with parameter \(p\) is greater than a Poisson random variable \(X\) with parameter \(\lambda\). The solution shows that \(\mathbb{P}(Y>X) = e^{-\lambda p}\). This result is derived by first determining \(\mathbb{P}(X \geq Y)\) using the probability mass functions for both distributions and applying the properties of exponential series. The final expression confirms the relationship between the parameters of the two distributions.

PREREQUISITES
  • Understanding of Poisson random variables and their probability mass function (pmf).
  • Familiarity with Geometric random variables and their probability mass function (pmf).
  • Knowledge of series expansions, particularly the exponential series.
  • Basic probability theory, including concepts of independence and cumulative distribution functions.
NEXT STEPS
  • Study the properties of Poisson random variables in detail, focusing on applications in queuing theory.
  • Learn about Geometric random variables and their applications in modeling success/failure scenarios.
  • Explore the concept of independence in probability and its implications for joint distributions.
  • Investigate the use of generating functions in probability theory for solving complex problems.
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Mathematicians, statisticians, and data scientists interested in probability theory, particularly those working with Poisson and Geometric distributions in statistical modeling and analysis.

Chris L T521
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Here's this week's problem!

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Problem: Let $X$ be a Poisson random variable with parameter $\lambda$, and let $Y$ be a Geometric random variable with parameter $p$ which is independent of $X$. In simplest terms of $\lambda$ and $p$, what is the value of $\Bbb{P}(Y>X)$?

Recall: The Poisson pmf is given by $f(x) = \dfrac{e^{-\lambda}\lambda^x}{x!}$ (with support $x\geq0$) and the Geometric pmf is given by $f(x) = p(1-p)^{x-1}$ (with support $x\geq 1$).

-----Remember to read the http://www.mathhelpboards.com/showthread.php?772-Problem-of-the-Week-%28POTW%29-Procedure-and-Guidelines to find out how to http://www.mathhelpboards.com/forms.php?do=form&fid=2!
 
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This week's problem was correctly answered by laura123. You can find her solution below.

[sp]$X$ is a Poisson random variable with parameter $\lambda$ and $Y$ is a Geometric random variable with parameter $p$ then $\mathbb{P}(X=n)=\dfrac{e^{-\lambda}\lambda^n}{n!}$ and $\mathbb{P}(Y=m)=pq^{m-1}$ where $q=1-p$, with $n\geq0$ and $m\geq 1$.
$\mathbb{P}(Y>X)=1-\mathbb{P}(X\geq Y)$. Let us find the value of $\mathbb{P}(X\geq Y)$:

$\begin{aligned}\displaystyle\mathbb{P}(X\geq Y) &= \sum_{n=1}^{+\infty}\mathbb{P}[X=n\wedge(Y=1\vee...\vee Y=n)]\\ &=\sum_{n=1}^{+\infty}\left[\dfrac{e^{-\lambda}\lambda^n}{n!}\cdot \sum_{m=1}^{n}pq^{m-1}\right]\\ & =\sum_{n=1}^{+\infty}\left[\dfrac{e^{-\lambda}\lambda^n}{n!}\cdot p \sum_{m=1}^{n}q^{m-1}\right]\\ & =\sum_{n=1}^{+\infty}\left[\dfrac{e^{-\lambda}\lambda^n}{n!}\cdot p \dfrac{1-q^n}{1-q}\right]\\ & =\sum_{n=1}^{+\infty}\left[\dfrac{e^{-\lambda}\lambda^n}{n!}\cdot p \dfrac{1-q^n}{1-1+p}\right]\\ & =\sum_{n=1}^{+\infty}\left[\dfrac{e^{-\lambda}\lambda^n}{n!} \cdot(1-q^n)\right] \\ & =
e^{-\lambda}\sum_{n=1}^{+\infty}\left[\dfrac{\lambda^n}{n!}\cdot(1-q^n)\right] \\ & =
e^{-\lambda}\sum_{n=1}^{+\infty}\left[\dfrac{\lambda^n}{n!}-\dfrac{\lambda^n}{n!}q^n\right] \\ & =
e^{-\lambda}\sum_{n=1}^{+\infty}\left[\dfrac{\lambda^n}{n!}-\dfrac{(\lambda q)^n}{n!}\right] \\ & =
e^{-\lambda}\left[\sum_{n=1}^{+\infty}\dfrac{\lambda^n}{n!}-\left(\sum_{n=1}^{+\infty}\dfrac{(\lambda q)^n}{n!}\right)\right]
\end{aligned}$

because $\displaystyle e^x-1=\sum_{n=1}^{+\infty}\dfrac{x^n}{n!}$ then $\displaystyle\sum_{n=1}^{+\infty}\dfrac{\lambda^n}{n!}=e^{\lambda}-1$ and $\displaystyle\sum_{n=1}^{+\infty}\dfrac{(\lambda q)^n}{n!}=e^{\lambda q}-1$.

Therefore
$\displaystyle e^{-\lambda}\left[\sum_{n=1}^{+\infty}\dfrac{\lambda^n}{n!}-\left(\sum_{n=1}^{+\infty}\dfrac{(\lambda q)^n}{n!}\right)\right]=
e^{-\lambda}[e^{\lambda}-1-e^{\lambda q}+1]=
e^{-\lambda}[e^{\lambda}-e^{\lambda q}]=
e^{-\lambda}[e^{\lambda}-e^{\lambda -\lambda p}]=
1-e^{-\lambda p}$.

Then $\mathbb{P}(Y>X)=1-\mathbb{P}(X\geq Y)=1-(1-e^{-\lambda p})=e^{-\lambda p}$[/sp]
 

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