Determine Joint Density & E[z] of f_xy(x,y) Function

In summary, the conversation discusses finding the joint density of two variables, wz, and the expected value of z. The solution involves a transformation to x=1-zy and y=w, with the Jacobian being -w. The resulting joint distribution is 24(1-zw)w^2 with bounds of 0<w<1 and 0<z<1. However, there seems to be an error in the integration process.
  • #1
cutesteph
63
0

Homework Statement



f_xy(x,y)= 24xy for o<x<1 and 0<y<1-x

let z=[1-x]/y and w=y

determine joint density of wz
and E(z)

Homework Equations





The Attempt at a Solution


E[z] = Integral [0,1] integral [0,1-x] 24xy*(1-x)/y dydx = 2

The joint distribution doing a transformation to x=1-zy and y =w so x = 1-wz

Jacobian = -w

so f_wz (wz) = 24(1-zw)w *|-w| = 24 (1-zw)w^2 the new bounds are 0<1-zw<1 => 1>zw>0 and 0<w<1-(1-zw) => 0<w<wz

the bounds are 0<w<1 and o<z<1 but the density is not equaling 1 so I am doing something wrong.
 
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  • #2
I don't understand how you got from:
cutesteph said:
the new bounds are 0<1-zw<1 => 1>zw>0 and 0<w<1-(1-zw) => 0<w<wz
which is right, to
the bounds are 0<w<1 and o<z<1
 
  • #3
So we have 1>zw>0 and zw>w>0

So 1>zw>w>0 => 1/w > z > 1 and it seems 1>w>0 but the integration does not work.
 
  • #4
cutesteph said:
So we have 1>zw>0 and zw>w>0

So 1>zw>w>0 => 1/w > z > 1 and it seems 1>w>0 but the integration does not work.
Your expression for joint pdf integrates to 1 for me. Please show your working,
 

Related to Determine Joint Density & E[z] of f_xy(x,y) Function

1. What is a joint density function?

A joint density function is a mathematical representation of the probability distribution of two or more random variables. It describes the likelihood of the simultaneous occurrence of multiple events.

2. How do you determine the joint density of a function?

To determine the joint density of a function, you must first find the marginal density functions of each individual variable. Then, you can use these functions to calculate the joint density function using the multiplication rule for independent events.

3. What does E[z] represent in the joint density function?

E[z] represents the expected value or mean of the joint density function. It is calculated by integrating the joint density function over all possible values of the variables.

4. How do you interpret the joint density function?

The joint density function provides information about the likelihood of multiple events occurring together. It can also be used to calculate the probability of specific combinations of events.

5. Can the joint density function be used for dependent variables?

Yes, the joint density function can be used for dependent variables. In this case, the calculation of the joint density function would involve taking into account the relationship between the variables, such as using conditional probabilities.

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