Are These Random Variables Independent or Identically Distributed?

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Homework Help Overview

The discussion revolves around the independence and distribution of three random variables, X, Y, and Z, defined over a sample space with equal probabilities. Participants explore whether these random variables have the same distribution and how to demonstrate independence or dependence between them.

Discussion Character

  • Conceptual clarification, Assumption checking, Mathematical reasoning

Approaches and Questions Raised

  • Some participants attempt to show that the random variables have the same distribution by calculating their expectations and comparing them.
  • Others question whether having the same expectation implies the same distribution, suggesting that counterexamples exist.
  • One participant seeks guidance on how to demonstrate independence by verifying Bienaymé's formula.
  • Another participant proposes using moment-generating functions to explore the distributions further.

Discussion Status

The discussion is active, with participants exploring various interpretations of the problem. Some have made progress on parts (a), (b), and (c), while there is ongoing inquiry about part (d) and the nature of independence between the random variables.

Contextual Notes

Participants are working within the constraints of a homework assignment, which includes specific tasks related to the properties of random variables and their distributions. There is an emphasis on verifying assumptions and definitions related to independence and distribution.

squenshl
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Homework Statement


Let [tex]\Omega[/tex] = {w1, w2, w3}, P(w1) = 1/3, P(w2) = 1/3, P(w3) = 1/3, and define X, Y, Z as follows:
X(w1) = 1, X(w2) = 2, X(w3) = 3
Y(w1) = 2, Y(w2) = 3, Y(w3) = 1
Z(w1) = 3, Z(w2) = 1, Z(w3) = 2

(a) Show that these 3 random variables have the same distribution.
(b) Find the probaility distribution of X+Y, Y+Z and X+Z.
(c) Show that X and Y are not independent by verifying that Bienaymé's formula doesn't hold.
(d) Find a random variable W such that X and W are independent.

Homework Equations


The Attempt at a Solution


For (a) do we just add the values of X(w1), X(w2) and X(w3) with the values of Y(w1), Y(w2) and Y(w3) and so on and so forth. Find out they add to the same values so they must have the same prob distn.
 
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Or is it for:
X: 1 x 1/3 + 2 x 1/3 + 3 x 1/3 = 2
Y: 2 x 1/3 + 3 x 1/3 + 1 x 1/3 = 2
Z: 3 x 1/3 + 1 x 1/3 + 2 x 1/3 = 2

Since the 3 random variables have the same expectation, they have the same probability distribution.
 
I have done (a), (b), (c) but how do I do (d). I was told to show that P(X [tex]\cap[/tex] W) = P(X)P(W) but how do I do that?
 
squenshl said:
Since the 3 random variables have the same expectation, they have the same probability distribution.

3 random variables with the same expectation do not necessarily have the same distribution. The expectation is just the mean, you can find a counter example to that easily. MGFs can show that distributions are the same?
 
squenshl said:

Homework Statement


Let [tex]\Omega[/tex] = {w1, w2, w3}, P(w1) = 1/3, P(w2) = 1/3, P(w3) = 1/3, and define X, Y, Z as follows:
X(w1) = 1, X(w2) = 2, X(w3) = 3
Y(w1) = 2, Y(w2) = 3, Y(w3) = 1
Z(w1) = 3, Z(w2) = 1, Z(w3) = 2

(a) Show that these 3 random variables have the same distribution.
(b) Find the probaility distribution of X+Y, Y+Z and X+Z.
(c) Show that X and Y are not independent by verifying that Bienaymé's formula doesn't hold.
(d) Find a random variable W such that X and W are independent.

Homework Equations





The Attempt at a Solution


For (a) do we just add the values of X(w1), X(w2) and X(w3) with the values of Y(w1), Y(w2) and Y(w3) and so on and so forth. Find out they add to the same values so they must have the same prob distn.

(a) P{X=1} = P(w_1) = 1/3, P{Y=1} = P(w_3) = 1/3, etc. So, they all have the same distribution.

(b) P{X+Y=2} = P{X=1 &Y=1} = P{w_1 & w_2} = 0, P{X+Y=3} + P{X=1 & Y=2} + P{X=2 & Y=1} = P{w_1 & w_1} + P{w_2 & w_3} = P{w_1} = 1/3. P{X+Y=4} = P{w_2 & w_2} = 1/3, and P{X+Y = 6} = P{w_3 & w_3} = 1/3, so the probabilities P{X+Y= = i} for i=2,3,4,5,6 are 1/3,0,1/3,0,1/3. You can do Y+Z and X+Z similarly.

(c) P{X=1 & Y=1} = 0, while P{X=1}*P{Y=1} = (1/3)^2 = 1/9.

(d) An obvious solution W = k (k = an arbitrary constant) for all three points w_i . This is a degenerate random variable. With more work (eg., using moment-generating functions) we can show that this is the _only_ solution.

R.G. Vickson
 

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