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

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SUMMARY

The discussion centers on the independence of the random variables z and w, defined as z = x + y and w = x - y, where x and y are independent and identically distributed exponential random variables. The consensus is that z and w are not independent due to their inherent relationship; the value of w is constrained by the value of z. The reasoning provided highlights that if z is fixed, w cannot take on arbitrary values, confirming their dependence. The discussion also touches on the tedious nature of calculating joint and marginal probability density functions (pdfs) to establish independence.

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  • Understanding of random variables and their distributions
  • Knowledge of joint and marginal probability density functions (pdfs)
  • Familiarity with the concept of independence in probability theory
  • Basic understanding of covariance and its implications for independence
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  • Study the derivation of joint and marginal pdfs for sums and differences of random variables
  • Explore the properties of exponential distributions, particularly in relation to independence
  • Learn about covariance and its role in determining the independence of random variables
  • Investigate examples of dependent and independent random variables to strengthen intuition
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Students and professionals in statistics, data science, and probability theory who seek to deepen their understanding of random variable independence and its implications in statistical analysis.

WolfOfTheSteps
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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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could you have a look at the covariance? - i think if events are independent the covariance should be zero
 

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