How to determine if random variables x,y,z are independent?

In summary, the conversation discusses the independence of continuous random variables x, y, and z, with the function f(x,y,z) defined as x^2e^{-x-xy-xz}. The marginal density functions are calculated and it is observed that if x,y,z>0, they are not independent. An alternative method for checking independence is suggested, but it is noted that picking the right values is important for this method to work. The validity of the original post is also questioned.
  • #1
lep11
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Let ##f(x,y,z)=x^2e^{-x-xy-xz}##, if ##x,y,z>0## and ##f(x,y,z)=0## otherwise. Are the continuous random variables ##x,y,z## independent or not?

Intuitively they are not independent. I calculated the marginal density functions:

##f_x(x)=\iint_{\Omega} f(x,y,z) dydz=e^{-x}##

##f_y(y)=\iint_{\Omega} f(x,y,z) dxdz=(y+1)^{-2}##

##f_z(z)=\iint_{\Omega} f(x,y,z) dxdy=(z+1)^{-2}##

Now we observe that if ##x,y,z>0##,

##(x,y,z)=x^2e^{-x-xy-xz}\neq{e^{-x}}(y+1)^{-2}(z+1)^{-2}##. Thus ##x,y,z## are not independent.
Is this correct?
Is there easier method to check if they are independent as this way is 'a bit tedious'?
 
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  • #2
If they are independent, then f(2,2,1)/f(1,2,1) = f(2,1,1)/f(1,1,1), which is easy to check. Picking the right values is the interesting part, because you don't gain anything if the equality holds.
 
  • #3
mfb said:
If they are independent, then f(2,2,1)/f(1,2,1) = f(2,1,1)/f(1,1,1), which is easy to check. Picking the right values is the interesting part, because you don't gain anything if the equality holds.
Did you arbitrarily pick the values of x,y and z? I checked and the equation holds. Is the original post o.k.?
 
  • #4
I picked them arbitrarly. I get $$\frac{4 e^{-8}}{e^{-4}} = \frac{4 e^{-6}}{e^{-3}}$$
Which is wrong.

Your method works as well, but it is more work.
 

1. How do I know if three random variables are independent?

To determine if three random variables x, y, and z are independent, you can use the following formula: P(x,y,z) = P(x) * P(y) * P(z). If this equation holds true, then the variables are considered independent. This means that the occurrence of one variable does not affect the likelihood of the other two variables occurring.

2. Can I use a correlation coefficient to determine independence?

No, correlation coefficients only measure the strength and direction of a linear relationship between two variables. They cannot determine if the variables are independent or not. To determine independence, you must use the formula mentioned in question 1.

3. What is the difference between independence and mutual exclusivity?

Independence means that the occurrence of one variable does not affect the likelihood of the other variable occurring. Mutual exclusivity, on the other hand, means that the two variables cannot occur simultaneously. While independence allows for the possibility of both variables occurring, mutual exclusivity does not.

4. How do I test for independence in a dataset?

To test for independence in a dataset, you can use a chi-square test. This test compares the observed frequencies of each variable to the expected frequencies calculated using the independence formula. If the calculated chi-square value is greater than the critical value, then the variables are considered dependent. If it is less than the critical value, then the variables are considered independent.

5. Can three dependent variables be considered independent?

No, if three variables are dependent, then they cannot be considered independent. The concept of independence means that the occurrence of one variable does not affect the likelihood of the other variable occurring. If three variables are dependent, then the occurrence of one variable will always affect the likelihood of the other two variables occurring.

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