Probability - Condition/Marginal density and Expectation

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SUMMARY

The discussion focuses on the analysis of continuous random variables X and Y with the joint probability density function defined as f(x,y) = 10x²y for 0 < x < y < 1. Key calculations include determining P(Y < X/2), conditional probabilities, marginal density functions, and expectations such as E[XY²] and E[Y|X]. The solutions involve integrating the joint density function and applying conditional probability formulas to derive the necessary results.

PREREQUISITES
  • Understanding of joint probability density functions
  • Knowledge of integration techniques for continuous functions
  • Familiarity with conditional probability and expectation
  • Basic concepts of marginal density functions
NEXT STEPS
  • Study the derivation of marginal density functions for continuous random variables
  • Learn about conditional expectation and its applications in probability theory
  • Explore integration techniques for calculating probabilities in multivariable calculus
  • Investigate the properties of joint distributions and their implications in statistics
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Students and professionals in statistics, data science, and applied mathematics who are working with probability theory and require a deeper understanding of joint and conditional distributions.

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Homework Statement



Let X and Y be contnious random variables with joint probability density function -

[tex]f(x,y) = 10x^2y[/tex] if 0<x<y<1 0 othewise

a) Determine [tex]P( Y < \frac{X}{2})[/tex]

b) Determine [tex]P(x \leq 1/2 | Y < X^2)[/tex]

c) Determine the marginal density functions of X and Y, respectively

d) Determine [tex]E[XY^2][/tex]

e) Determine [tex]E[Y|X = x][/tex]

g) Obtaine the probability density function of E[Y|X]

Homework Equations





The Attempt at a Solution



Did I set up the a - f correctly?

a)

[tex]\int^1_0\int^{X/2}_0 10x^2y dy dx[/tex]

b) [tex]P(A|B) = \frac{P(A \cap B)}{P(B)} \rightarrow \frac{P(X \leq 1/2 \cap Y < X^2)}{P(Y < X^2)}[/tex]

c)

[tex]F_Y (y) = \int^1_y 10x^2y dx[/tex] [tex]F_X (x) = \int^x_0 10x^2y dy[/tex]

d)
[tex]E[XY^2] = \int^1_0\int^x_0 xy^2 10x^2y dy dx[/tex]

e)

[tex]F_{Y|X} (Y|X) = \frac{f(x,y)}{F_X (x)}[/tex]

f)

[tex]E[Y|X] = \int^y_0 y F_{Y|X} (Y|X) dy[/tex]

g) Not sure how to do this one.
 
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Any suggestions?

Got a type

e) Determine conditional density function of Y given X = x.

f) Detetmine E[Y|X]
 

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