Calculating Marginal Probability Mass Functions for Discrete Random Variables

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SUMMARY

The discussion focuses on calculating the marginal probability mass functions (PMFs) for two discrete random variables, X and Y, given the joint PMF defined as p(x,y) = ([5^x][7^y][e^-5])/x!(y-x)!. The user seeks to find the marginal PMFs p(x) and p(y) by integrating out the dependence on the second variable, using the formulas p(x)=∑(y≥x)p(x,y) and p(y)=∑(x≤y)p(x,y). It is noted that the joint PMF does not sum to one, but rather to e^37, raising questions about the integration of factorials in the calculations.

PREREQUISITES
  • Understanding of joint probability mass functions
  • Knowledge of marginal probability concepts
  • Familiarity with summation notation in probability
  • Basic skills in calculus and factorial manipulation
NEXT STEPS
  • Study the derivation of marginal PMFs from joint PMFs
  • Learn about the properties of discrete random variables
  • Explore the concept of normalization in probability distributions
  • Investigate techniques for summing series involving factorials
USEFUL FOR

Statisticians, data scientists, and students studying probability theory who need to understand the calculation of marginal PMFs for discrete random variables.

Mathemag1c1an
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I have this question which I cannot seem to solve:
The joint probability mass function p(x, y) of two discrete random variables X and Y is given by.
p(x,y) = ([5^x][7^y][e^-5])/x!(y-x)!
x and y are non-negative integers and x <= y
(i) Find the marginal probability mass functions of X and Y.
 
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You would have to "integrate out" the dependence on the second variable. Explicitly

[tex] p(x)=\sum_{y\geq x}p(x,y)[/tex]
and
[tex] p(y)=\sum_{x\leq y}p(x,y)[/tex]
By the way, you joint pmf doesn't sum to one, but to e37.
 
but how do i integrate the factorials?
 

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