Find the Probability: P(X<1/2 | Y=1)

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In summary, the conversation discusses finding the probability of X being less than 1/2 given that Y is equal to 1, using the definition of conditional probability and the given joint density function for X and Y. The summary also mentions the marginal density of Y and the conditional density of X given Y=y, and concludes that the two formulas for the conditional density will always be the same if correctly derived from the joint density function.
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kingwinner
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Homework Statement


Suppose X and Y are jointly continuous random variables with joint density function
f(x,y)=6x2y, 0<x<y, x+y<2
f(x,y)=0, otherwise
Find P(X<1/2 | Y=1).


Homework Equations


The Attempt at a Solution


By definition,
P(X<1/2 | Y=1)
1/2
=∫ fX|Y(x|y=1) dx
-∞

My computations:
Marginal density of Y:
fY(y)=2y^4, 0<y<1
fY(y)=2y(2-y)^3, 1<y<2


Condition density of X given Y=y:
Case 1: For given/fixed 0<y<1,
fX|Y(x|y)=3x^2 / y^3, 0<x<y

Case 2: For given/fixed 1<y<2,
fX|Y(x|y)=3x^2 / (2-y)^3, 0<x<2-y

I hope these are correct. Now P(X<1/2 | Y=1) is the troublesome case because we are given Y=1, which formula for fX|Y(x|y) should I use?


Thanks for any help!
 
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  • #2
Your two formulas are the same at y=1, so it doesn't matter which one you use!
 
  • #3
OK, but in general will they always be the same? What should we do in such a case in general?
 
  • #4
If correctly derived from a given joint density function, yes, they must be the same.
 
  • #5
um...Any proof about it?
 

1. What does "P(X<1/2 | Y=1)" mean?

"P(X<1/2 | Y=1)" is a notation used in probability to represent the probability that the value of a random variable X is less than 1/2, given that another random variable Y has a value of 1. Essentially, it is asking for the probability of an event occurring (X<1/2), given that we know another event (Y=1) has already occurred.

2. How is the probability calculated in this equation?

The probability is calculated by dividing the number of favorable outcomes (where X<1/2 and Y=1) by the total number of possible outcomes. This is known as the conditional probability formula: P(X<1/2 | Y=1) = P(X<1/2 and Y=1) / P(Y=1).

3. Can the probability be greater than 1 in this equation?

No, the probability cannot be greater than 1 in this equation. The maximum value for a probability is 1, which represents a 100% chance of an event occurring. If the calculated probability for P(X<1/2 | Y=1) is greater than 1, then it is likely that an error has been made in the calculation.

4. How is this type of probability used in real-world situations?

Conditional probability, as represented by "P(X<1/2 | Y=1)", is used in various fields of science, such as biology, psychology, and economics. For example, it can be used to determine the likelihood of a patient having a certain disease (X) given their symptoms (Y), or the probability of a stock market crashing (X) given a certain economic indicator (Y).

5. What affects the value of "P(X<1/2 | Y=1)"?

The value of "P(X<1/2 | Y=1)" is affected by the relationship between the two events, X and Y. If they are independent events, the probability will be equal to the unconditional probability of X being less than 1/2. However, if they are dependent events, the probability will be affected by the likelihood of Y occurring. Additionally, the sample size and the accuracy of the data used in the calculation can also affect the value of the probability.

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