Correlation of Two Random Vectors

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SUMMARY

The discussion centers on the correlation of two random vectors, \(X\) and \(Y\), defined as \(X = aR + N\) and \(Y = bG + W\). Here, \(R\) and \(G\) are strongly correlated random vectors averaging to the zero vector, while \(N\) and \(W\) are independent vectors of i.i.d. normal random variables. The participants confirm that \(X\) and \(Y\) are indeed correlated, as indicated by the expectation \(E((X-\overline{X})(Y-\overline{Y})^t) \neq \mathbf{0}\).

PREREQUISITES
  • Understanding of random vectors and their properties
  • Knowledge of correlation and covariance concepts
  • Familiarity with statistical notation and expectations
  • Basic grasp of independent and identically distributed (i.i.d.) random variables
NEXT STEPS
  • Study the mathematical definition of correlation in random variables
  • Explore the properties of covariance matrices
  • Learn about the implications of linear combinations of random variables
  • Investigate the concept of independence in probability theory
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Statisticians, data scientists, and students in quantitative fields who are interested in understanding the correlation between random variables and their applications in statistical analysis.

OhMyMarkov
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Hello everyone!

I'm coming to notice day by day how our education is purely focused on memorizing and applying formulas rather than understanding the concept. Assume we have the following:

$X = aR + N$, and
$Y = bG + W$,

where $X, Y$ are random vectors, $R, G$ are strongly correlated random vector that average out to the zero vector each, $a, b$ are scalars, and $N, W$ are two independent vectors of i.i.d. normal RVs.

Now, $X$ and $Y$ are correlated, right?
 
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OhMyMarkov said:
Hello everyone!

I'm coming to notice day by day how our education is purely focused on memorizing and applying formulas rather than understanding the concept. Assume we have the following:

$X = aR + N$, and
$Y = bG + W$,

where $X, Y$ are random vectors, $R, G$ are strongly correlated random vector that average out to the zero vector each, $a, b$ are scalars, and $N, W$ are two independent vectors of i.i.d. normal RVs.

Now, $X$ and $Y$ are correlated, right?

I somehow suspect you have missed out some information, but under my interpretation of what you mean, yes.

If you write out what you mean by correlation it should be obvious what the answer is.

CB

PS My interpretation of what you mean when you ask are X and Y correlated is that you are asking: is \( E( (X-\overline{X}) (Y-\overline{Y})^t)\ne {\bf{0}} \)?
 
Last edited:
Yes, this is what I mean. Wanted to make sure... I'll review the problem...
 

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