Calculating Joint Probability for f(x,y) = 4xy with X<Y in 0<x<1 and 0<y<1

In summary, joint probability is the likelihood that two events will occur simultaneously and is calculated by multiplying the probabilities of each individual event. To calculate joint probability for a continuous distribution, the limits of integration for both x and y must be found and the formula P(X<Y) = ∫∫4xy dxdy with the limits of integration is used. X<Y in the given function means that the value of X is less than the value of Y and this is a condition that must be satisfied for the function to hold true. Joint probability cannot be greater than 1 since probabilities are always between 0 and 1. It is useful in scientific research for analyzing the likelihood of multiple events occurring together and understanding the relationships between different
  • #1
kasse
384
1
If

f(x,y) = 4xy, for 0<x<1, 0<y<1
f(x,y) = 0, elsewhere

What's the probability that X<Y?

It seems likely that the probability is 0.5, but how can I show it matematically?
 
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  • #2
Hi Kasse,

If f is the joint probability density function, then P(X<Y) is the double integral of f(x,y) over the region in the unit square given by y>x.
 

1. What is joint probability?

Joint probability is the likelihood that two events will occur simultaneously. It is calculated by multiplying the probabilities of each individual event.

2. How do you calculate joint probability?

To calculate joint probability for a continuous distribution, such as f(x,y) = 4xy with X

3. What does X

In the given function, X

4. Can joint probability be greater than 1?

No, joint probability cannot be greater than 1. Since probabilities are always between 0 and 1, the product of two probabilities will also be between 0 and 1.

5. How is joint probability useful in scientific research?

Joint probability is useful in scientific research because it allows us to analyze the likelihood of multiple events occurring together. This can help us understand the relationships between different variables and make predictions about future outcomes.

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