Joint Probability Distributions

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SUMMARY

The discussion centers on the calculation of joint probability distributions, specifically addressing the formula P_{(\xi1,\xi2)}(x1,x2)=P_{(\xi1)}(x1)P_{(\xi2)}(x2). The participant initially misapplied this formula, assuming it applied to dependent variables, which led to confusion regarding the probabilities of specific outcomes. Upon clarification, it was established that this formula is only valid for independent variables, highlighting the importance of understanding variable dependence in probability calculations.

PREREQUISITES
  • Understanding of joint probability distributions
  • Knowledge of independent and dependent variables in probability theory
  • Familiarity with probability notation and terminology
  • Basic statistical concepts related to probability calculations
NEXT STEPS
  • Study the differences between independent and dependent random variables
  • Learn about conditional probability and its applications
  • Explore the concept of marginal distributions in probability
  • Review examples of joint probability distributions in real-world scenarios
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Students of statistics, data scientists, and anyone involved in probability theory who seeks to deepen their understanding of joint distributions and their applications in various contexts.

Carla1985
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I have this question:

View attachment 690and I'm a little confused. To calculate joint distributions in the earlier questions i was using:P_{(\xi1,\xi2)}(x1,x2)=P_{(\xi1)}(x1)P_{(\xi2)}(x2)But that would mean that if:P_{(\xi1,\xi2)}(2,0)=0\ either\ P_{(\xi1)}(2)=0\ or\ P_{(\xi2)}(0)=0which can't be true in either case as P_{(\xi1,\xi2)}(1,0)\ isnt\ 0\ and\ neither\ is\ P_{(\xi1,\xi2)}(2,1)Can someone please explain what I'm missing. Thanks :/
 

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Nevermind, I found my mistake. This was only for independent variables, which these obviously aren't :)
 

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