Joint Density problem again: What am I doing wrong?

In summary: This means that the probability of u is constant between 0 and 1, and the probability of v decreases as v increases. To find the expected values, you integrate over the respective intervals: E(u) = \int_0^1 u(1)du = 1/2 and E(v) = \int_0^1 v(-\ln v)dv = 1/4. In summary, the joint density of two random variables, U and V, is given by f(u,v) = 1/u for 0 < v < u < 1. The marginal densities of U and V are g(u) = 1 and h(v) = -ln(v), respectively. The expected values for U
  • #1
hwill205
11
0
Hello,

I would gladly appreciate any and all help with this joint density problem a practice problem for an exam. Please excuse my lack of use of the proper symbols, I don't know how to express them online unfortunately :

Joint Density of two random variables, U and V is:

f(u,v)= 1/u for 0<v<u, and 0<u<1

1. Find marginal densities of U and V.

For marginal density of u, I did the integral of 1/u with respect to v from 0 to u. I got the integral to be v/u. And then when you plug in 0 and u, I got 1. This doesn't look right to me at all.

For the marginal density of v, I did the the integral of 1/u with respect to u and I got ln(u). I then plugged in 0 and 1 and I got 0. For the ln u, when I plugged in the 0, I just did the limit as u approaches 0 and that is zero. So it should be 0-0, which is zero.

Does this even look remotely correct? I don't believe it is.

2. Find E(u) and E(v)

For E(u), I just did the double integral (from 0 to 1 and 0 to u) of 1, since u*(1/u) equals 1. I got 1/2.

For E(v), I did the double integral (from 0 to 1 and 0 to u) of v/u and I got 1/8.

Again, these answers don't look right. Any and all help is GREATLY appreciated.
 
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  • #2
To find the density of [tex] u [/tex] you need to integrate the joint density with respect to [tex] v [/tex] over its range: since you know [tex] 0 < v < u < 1 [/tex], you know the integrals limits.

Similarly, to find the density of [tex] v [/tex] you integrate the joint density over the range of [tex] u [/tex]. Try for the densities again.
 
  • #3
Ok I tried it again and this is what I get

marginal density of u= Integral (from 0 to u) of 1/u dv. For that I get v/u and I plug in the 0 and u. I am still getting 1.

marginal density of v= Integral (from v to 1) of 1/u du. This is ln (u). Plugging in v and 1, I got - ln(v) for my answer.


These still don't seem right.
 
  • #4
so for 0<u<1
[tex] p(u)du = (\int p(u,v) dv)du = (\int_0^u 1/u dv)du = (v/u)_0^u du = du[/tex]
so the marginal density of u is constant between 0 and 1

note its is correctly normalised and intuitively makes sense. p(u,v) is only defined on the traingle bounded by u=0, u=v and u=1, with amplitude 1/u

The marginal density is the probailty of u, reagrdless of v. It will be proportional to the volume of a vertical sliver for the triangle, the length along the v axis will be u (as the line u=v), the length along the u axis is du, and the height is 1/u, given p(u)du = (u)(1/u)du = du
 
Last edited:
  • #5
hwill205 said:
Ok I tried it again and this is what I get

marginal density of u= Integral (from 0 to u) of 1/u dv. For that I get v/u and I plug in the 0 and u. I am still getting 1.

marginal density of v= Integral (from v to 1) of 1/u du. This is ln (u). Plugging in v and 1, I got - ln(v) for my answer.


These still don't seem right.

Yes, the marginal density of u is [tex] g(u) = 1, \quad 0 < u < 1 [/tex] (makes more sense when you write out the interval). And, the marginal density of v is [tex] h(v) = -\ln v, \quad 0 < 1[/tex].
 

1. What is the Joint Density problem and how is it related to statistics?

The Joint Density problem is a common problem in statistics that deals with finding the probability of multiple events occurring together. It involves using joint probability distributions to determine the likelihood of two or more variables occurring simultaneously.

2. What are the key steps to solving a Joint Density problem?

The key steps to solving a Joint Density problem include identifying the variables, understanding the relationship between the variables, determining the joint probability distribution, and using the appropriate formula or method to calculate the probability of the events occurring together.

3. What are some common mistakes made when solving a Joint Density problem?

Some common mistakes made when solving a Joint Density problem include using the wrong formula or method, not properly understanding the relationship between the variables, and not taking into account all the necessary information given in the problem.

4. How can I improve my understanding of Joint Density problems?

To improve your understanding of Joint Density problems, it is important to practice solving various types of problems and to familiarize yourself with different methods and formulas. It is also helpful to seek out additional resources, such as textbooks or online tutorials, for further explanation and practice.

5. What are some real-world applications of Joint Density problems?

Joint Density problems have many real-world applications, especially in fields such as finance, economics, and engineering. They can be used to analyze and predict the likelihood of events occurring together, such as stock market trends, economic indicators, or the failure of mechanical systems.

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