Expected Value and Conditional Probability

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SUMMARY

The discussion centers on calculating the expected value E[XY] using the identity E[XY] = E[E(XY/Y)] = E[Y[E(X/Y)]]. The user seeks to simplify the process of finding E[XY] by leveraging previously calculated values, specifically E[X/Y] = Y, leading to the conclusion that E[XY] simplifies to E[Y^2]. This approach effectively reduces the complexity of the integral typically required for such calculations.

PREREQUISITES
  • Understanding of expected value and its properties
  • Familiarity with conditional probability concepts
  • Knowledge of integrals and their application in probability theory
  • Basic proficiency in mathematical notation and identities
NEXT STEPS
  • Study the derivation and applications of the law of total expectation
  • Explore advanced topics in conditional expectation
  • Learn about variance and its relationship with expected values
  • Investigate the use of moment-generating functions in probability
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Students and professionals in statistics, data science, and mathematics who are looking to deepen their understanding of expected values and conditional probability techniques.

retspool
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So i a need to find E[XY], expected value of XY

But the process of finding E[X] includes a long and tideous integral which i am trying to avoid.
So computing E[XY] using its formula is also something i am trying to avoid.

But could i use this identity?

E[XY] = E[E(XY/Y)] = E[Y[E(X/Y)]]

Since I've already found E[X/Y] = Y, it gives me E[Y.Y] = E[Y^2].

Is the identity true?
 
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I deduced the identity from the given formula

E[X] = E(E[XY/Y])
 

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