Covariance/ Correlation Calculation

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SUMMARY

The discussion focuses on calculating the covariance and correlation between two random variables, N (number of users logged on) and T (time until the next log-off), using the joint probability function P(N=η, X≤t) = (1-ρ)ρ^{η-1}(1-e^{-ηλt}). The formulas for covariance COV(X,Y) = E[XY]-E[X]E[Y] and correlation ρ_{X,Y} = (E[XY]-E[X]E[Y])/(σ_{X}σ_{Y}) are established. The expected value E[XY] is derived from the joint probability density function (PDF), with guidance requested on integrating the joint PDF for expected value calculations.

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ewoeckel
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1. Let N and T be the number of users logged on and the time until the next log-off. The joint probability of N and T is given by P(N=η, X≤t) = (1-ρ)ρ^{η-1}(1-e^{-ηλt}) for η=1,2,...;t>0.) Find the correlation and covariance of N and T.

2. COV(X,Y) = E[XY]-E[X]E[Y]
ρ_{X,Y} = (E[XY]-E[X]E[Y])/(σ_{X}σ_{Y})
E[XY] = ∫∫ xy f_{XY}(x,y) dx dy


3. I do not know how to find the expected value from the joint PDF and was hoping for some guidance.
 
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Same as with a single variable PDF. Assume f(x,y) is the normalized PDF

E[x]=\int x f(x,y) dx dy, etc.

But remember that "your PDF" is *not* a true PDF, it is integrated for t! (X<=t)!
 

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