Expected value and joint probability density function

In summary, the joint probability density function for two uniformly distributed random variables on a circle with radius a is given by f(x,y) = \frac{1}{\pi a^2}, x^2 + y^2 <= a^2 and 0 otherwise. To find the expected value of X, the integral \int^{\infty}_{- \infty}\int^{\infty}_{- \infty}\frac{x}{\pi a^2} dxdy is incorrect as the probability outside the circle is 0. Instead, the integral in polar coordinates would be used with the limits of integration covering the circle of radius a.
  • #1
kasse
384
1
Assume that two random variables (X,Y) are uniformly distributed on a circle with radius a. Then the joint probability density function is

[tex]f(x,y) = \frac{1}{\pi a^2}, x^2 + y^2 <= a^2[/tex]
[tex]f(x,y) = 0, otherwise[/tex]

Find the expected value of X.


E(X) = [tex]\int^{\infty}_{- \infty}\int^{\infty}_{- \infty}\frac{x}{\pi a^2} dxdy[/tex]

Is this correct so far? What are the limits of the integral supposed to be?
 
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  • #2
Since your pdf is nonzero only on the circle, I think this is what you want:
[tex]\int^{a}_{-a}\int^{\sqrt{a^2 - y^2}}_{- \sqrt{a^2 - y^2}}\frac{x}{\pi a^2} dxdy[/tex]
 
  • #3
I think this integral would be easier in polar coordinates.
 
  • #4
kasse said:
Assume that two random variables (X,Y) are uniformly distributed on a circle with radius a. Then the joint probability density function is

[tex]f(x,y) = \frac{1}{\pi a^2}, x^2 + y^2 <= a^2[/tex]
[tex]f(x,y) = 0, otherwise[/tex]

Find the expected value of X.


E(X) = [tex]\int^{\infty}_{- \infty}\int^{\infty}_{- \infty}\frac{x}{\pi a^2} dxdy[/tex]

Is this correct so far? What are the limits of the integral supposed to be?
No that is not correct because the limits of integration cannot be from [itex]-\infty[/itex] to [itex]\infty[/itex]. The probability outside the circle of radius a is 0, not [itex]1/(\pi a^2)[/itex].

In polar coordinates the integral would be
[tex]\frac{1}{\pi a^2}\int_r\int_\theta r cos(\theta) (r drd\theta)[/tex]
and you want to cover the circle of radius a. What are the limits of integration for that?
 
  • #5
Thanks!
 

1. What is expected value?

Expected value is a measure of the central tendency of a probability distribution. It represents the average value that would be obtained from a large number of trials of a random experiment.

2. What is the formula for calculating expected value?

The formula for calculating expected value is the sum of all possible outcomes multiplied by their respective probabilities. This can be represented as E(X) = Σx * P(X=x), where X is the random variable and P(X=x) is the probability of X taking on a particular value x.

3. How is expected value different from actual value?

Expected value is a theoretical concept that represents the long-term average value of a random experiment. Actual value, on the other hand, is the specific value that is observed or obtained in a single trial of the experiment.

4. What is a joint probability density function?

A joint probability density function is a function that describes the simultaneous probability distribution of two or more random variables. It is used to calculate the probability of obtaining a particular combination of values for the variables.

5. How is joint probability density function used in decision making?

Joint probability density function is used in decision making to assess the likelihood of different outcomes and make informed choices. It can help in determining the optimal course of action by considering the potential risks and rewards associated with each outcome.

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