- #1
OhMyMarkov
- 83
- 0
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'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?