SUMMARY
The discussion focuses on calculating the expected value of the random variable X given that Y equals 5, using the joint probability density function (pdf) f(x,y) = 1/50 for 0 < x < 10, 0 < y < 10, and 0 < x + y < 10. The correct approach involves determining the marginal pdf f(y) and the conditional expectation E[X|Y]. Participants clarify that the limits of integration for calculating E[X|Y=5] should be from 0 to 5, not 0 to 10. The final expected value calculation yields E[X|Y=5] = 10, but this result is questioned and requires careful verification of each step in the integration process.
PREREQUISITES
- Understanding of joint probability density functions (pdf)
- Knowledge of conditional expectation calculations
- Familiarity with integration techniques in probability theory
- Ability to interpret and manipulate LaTeX for mathematical expressions
NEXT STEPS
- Review the derivation of marginal and conditional probability density functions
- Practice calculating expected values using different joint pdfs
- Learn about the properties of integrals in probability theory
- Explore common pitfalls in LaTeX formatting for mathematical expressions
USEFUL FOR
Students studying probability theory, statisticians, and anyone involved in statistical analysis or mathematical modeling requiring an understanding of expected values and joint distributions.