The Independence of z and w: A Scientist's Perspective

In summary, the conversation discusses whether two variables, z and w, are independent given that they are defined in terms of two other independent and identically distributed exponential random variables, x and y. The initial question is whether it is necessary to find the joint pdf of z and w and compare it to the marginal pdfs, or if there is a simpler way to determine independence. The second speaker proposes a reasoning that looks at how the variables are constrained by each other, and concludes that they are not independent. The conversation then shifts to discussing the covariance and its relationship to independence.
  • #1
WolfOfTheSteps
138
0
If x and y are independent and identically distributed exponential random variables, and

z = x+y
w = x-y

are z and w also independent?

Do I have to actually find the joint pdf of z and w, then find the marginals and then see if they multiply to equal the joint pdf?

Or is there a way to just look at z and w and say whether they are independent or not?

I'm thinking like this: say z = 10... then w could be 5-5=0, but it could also be 10-0=10, or 3-7=-4. So w can be different things when z equals a certain number, but nonetheless it is still constrained by the value of z, so therefore they are not independent. (for example, if z = 10, w could never be 1000)

Is this reasoning correct? I know the definition of independence, but I believe that I have a very poor intuition of it. It's also pretty tedious to do the joint pdf to marginal pdfs comparison, if I could instead figure some of this stuff out by simple argument.
 
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  • #2
could you have a look at the covariance? - i think if events are independent the covariance should be zero
 

What are independent random variables?

Independent random variables are variables in a statistical experiment that have no influence on each other. This means that the outcome of one variable does not affect the outcome of the other variable.

How do you determine if two random variables are independent?

To determine if two random variables are independent, you can use the formula P(A ∩ B) = P(A) * P(B). If this equation holds true, then the two variables are considered independent.

Why is independence important in statistics?

Independence is important in statistics because it allows for more accurate and reliable results. If variables are not independent, it can lead to biased and incorrect conclusions.

Can two independent random variables be correlated?

Yes, two independent random variables can be correlated. Correlation measures the strength of a linear relationship between two variables, while independence measures the lack of relationship between variables. Therefore, it is possible for two variables to be independent but still have some level of correlation.

How are independent random variables used in real-world applications?

Independent random variables are used in a variety of real-world applications, such as in finance, medicine, and engineering. They are often used in statistical models to predict outcomes and make informed decisions.

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