How Do You Calculate P(Y>0.5|Y>X^2) for Uniformly Distributed Variables?

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SUMMARY

The calculation of P(Y>0.5|Y>X^2) for independent uniformly distributed variables X and Y on the interval (0, 1) involves evaluating the conditional probability using integrals. The correct formulation is P(Y > 0.5 ∩ Y > X^2) / P(Y > X^2), which simplifies to the integral expression: ∫(1/2 to 1) ∫(0 to √y) dx dy divided by ∫(0 to 1) ∫(0 to √y) dx dy. The final computed probability is approximately 0.6465, confirming the proper bounds for x in the integrals.

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Homework Statement



X and Y are independent and uniformly distributed on the unit interval (0, 1)

Determine P(Y>0.5|Y>X^2)

Homework Equations





The Attempt at a Solution



I set it up as the following: [tex]\frac{P(Y > 0.5 \cup Y > X^2)}{P(Y > X^2)}<br /> = \frac{\int^1_{1/2} \int^{\sqrt{y}}_0 dx dy}{\int^1_{0} \int^{\sqrt{y}}_0 dx dy}[/tex]

for the final answer I got ~0.6465. Did I make any mistakes?

The only thing that's bugging me is whether or not x is properly bounded in the integral. In the question y > x^2, so I assumed the square root of y is also greater than x. And since x is between 0 and 1, I believe that 0<x<sqrt(y)
 
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Your answer looks fine to me, but the union in this probability
[tex]\frac{P(Y > 0.5 \cup Y > X^2)}{P(Y > X^2)} = \frac{\int^1_{1/2} \int^{\sqrt{y}}_0 dx dy}{\int^1_{0} \int^{\sqrt{y}}_0 dx dy}[/tex]
should be an intersection
[tex]\frac{P(Y > 0.5 \cap Y > X^2)}{P(Y > X^2)} = \frac{\int^1_{1/2} \int^{\sqrt{y}}_0 dx dy}{\int^1_{0} \int^{\sqrt{y}}_0 dx dy}[/tex]
 
Thanks for the correction.
 

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