Correlation of Two Random Vectors

In summary, the conversation discusses the observation that education often focuses on memorizing and applying formulas rather than understanding concepts. The conversation then goes on to discuss a problem involving random vectors and correlation, with the conclusion that the vectors in question are indeed correlated.
  • #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?
 
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  • #2
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:
  • #3
Yes, this is what I mean. Wanted to make sure... I'll review the problem...
 

FAQ: Correlation of Two Random Vectors

What is correlation of two random vectors?

Correlation of two random vectors is a statistical measure that indicates the degree to which the variables are related or associated with each other. It measures the strength and direction of the linear relationship between two variables.

How is correlation of two random vectors calculated?

The correlation of two random vectors is calculated by dividing the covariance of the two variables by the product of their standard deviations. This results in a value between -1 and 1, where a positive value indicates a positive correlation, a negative value indicates a negative correlation, and a value of 0 indicates no correlation.

What is the difference between correlation and causation?

Correlation does not imply causation. While correlation measures the relationship between two variables, it does not necessarily mean that one variable causes the other. There could be other factors or variables that are responsible for the observed correlation.

What is the significance of correlation of two random vectors?

The significance of correlation of two random vectors is that it helps us understand the relationship between two variables. It can be used to identify patterns and make predictions based on the strength and direction of the correlation. It is also used in various statistical analyses and models.

What are the limitations of correlation of two random vectors?

Correlation of two random vectors only measures the linear relationship between two variables and does not take into account other types of relationships. It is also influenced by outliers in the data and does not indicate causation. It is important to carefully interpret the results of correlation and not make assumptions based on it.

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