Independent Poisson Processes Word Problem

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SUMMARY

This discussion focuses on calculating the probability of team B winning over team A in a football game modeled by independent Poisson processes. Team A's score follows a Poisson distribution with parameter λ_A, while team B's score follows a Poisson distribution with parameter λ_B. The correct approach involves calculating the probabilities Pr(X_A = 2) and Pr(X_B = 3) using the formulas Pr(X_A = k) = (λ_A^k * e^(-λ_A)) / k! and Pr(X_B = k) = (λ_B^k * e^(-λ_B)) / k!. The final probability that team B wins with a score of 3-2 is given by the product of these two probabilities.

PREREQUISITES
  • Understanding of Poisson processes and their parameters (λ_A and λ_B).
  • Familiarity with probability mass functions for discrete random variables.
  • Knowledge of basic calculus, particularly exponential functions.
  • Ability to manipulate factorials in probability calculations.
NEXT STEPS
  • Study the properties of Poisson distributions in detail.
  • Learn how to derive and apply the probability mass function for Poisson processes.
  • Explore the concept of independence in probability theory.
  • Investigate real-world applications of Poisson processes in sports analytics.
USEFUL FOR

This discussion is beneficial for students in introductory mathematical statistics, particularly those studying Poisson processes, as well as educators and anyone interested in applying statistical methods to sports outcomes.

Ocifer
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Hello, hopefully this is the right place. This is a homework question, so it should definitely be in this forum, but I wasn't sure which sub-forum to put this rather elementary stats question.

Homework Statement


In my introductory mathematical statistics class, we've been given the following word problem having to do with Poisson processes.

We are to consider a football game, where each team's score follows its own Poisson process. So there are two teams, team A and team B and, each team's final score has its own lambda parameter:

Team A scores \lambda_A goals per game.
Team B scores \lambda_B goals per game.

What is the probability of team B winning over team A, with a final score of 3-2.

Homework Equations


The Attempt at a Solution


My intuition (which I would like to confirm/have critiqued) is that since the processes are independent of each other I should find the following.

Let X_A be the final score of team A
Let X_B be the final score of team B

<br /> Pr(X_A = 2) = \lambda_A ^ 2 e^{- \lambda_A } / 2!<br />
<br /> Pr(X_B = 2) = \lambda_B ^ 3 e^{- \lambda_B } / 3!<br />

And then the probability that team B wins with a score of 3 to 2 is simply the product of the two probabilities above, namely:

<br /> Pr(X_A = 2 \cap X_B = 3) = Pr(X_A = 2) \cdot Pr(X_B = 3)<br />

Is this the correct approach?
 
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Ocifer said:
Hello, hopefully this is the right place. This is a homework question, so it should definitely be in this forum, but I wasn't sure which sub-forum to put this rather elementary stats question.

Homework Statement


In my introductory mathematical statistics class, we've been given the following word problem having to do with Poisson processes.

We are to consider a football game, where each team's score follows its own Poisson process. So there are two teams, team A and team B and, each team's final score has its own lambda parameter:

Team A scores \lambda_A goals per game.
Team B scores \lambda_B goals per game.

What is the probability of team B winning over team A, with a final score of 3-2.

Homework Equations


The Attempt at a Solution


My intuition (which I would like to confirm/have critiqued) is that since the processes are independent of each other I should find the following.

Let X_A be the final score of team A
Let X_B be the final score of team B

<br /> Pr(X_A = 2) = \lambda_A ^ 2 e^{- \lambda_A } / 2!<br />
<br /> Pr(X_B = 2) = \lambda_B ^ 3 e^{- \lambda_B } / 3!<br />

And then the probability that team B wins with a score of 3 to 2 is simply the product of the two probabilities above, namely:

<br /> Pr(X_A = 2 \cap X_B = 3) = Pr(X_A = 2) \cdot Pr(X_B = 3)<br />

Is this the correct approach?

Yes, it is correct (given the rather unlikely scenario that the two scores are independent).

RGV
 

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