Correlation and convolution (function or number)

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Correlation can be viewed as either a numerical coefficient or a function, depending on the context of the random variables involved. When considering independent random variables, correlation is represented as a number, while in stochastic processes, it becomes a function of the process's parameters. An autocorrelation correlogram illustrates the correlation between terms in the same stochastic process, presenting it as a function. Convolution, on the other hand, is a specific integration process that can yield a correlation based on the functions involved. Understanding these distinctions is crucial for interpreting statistical relationships accurately.
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I have a problem about correlation depending whether it it observed as a measurement of linear fit of statistical data, and when observed as a relationship between two continuous functions.

Is a result of correlation a coefficient (Pearson's product-moment coefficient) or a function?
If the correlation is a number, what information does a autocorrelation correlogram represent?

And if correlation is a number, why is convolution a function then?

tnx
 
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A correlation is a relationship between a pair of random variables.

If these are stand alone, it is a number.

If the random variables are elements of a stochastic process, the the correlation will be a function of the parameters of the stochastic process.

If the random variables are terms in the same stochastic process, then the correlation is an auto-correlation function.

A convolution is a particular kind of integration process. The result may be a correlation, depending on what functions are involved.
 
Here is a little puzzle from the book 100 Geometric Games by Pierre Berloquin. The side of a small square is one meter long and the side of a larger square one and a half meters long. One vertex of the large square is at the center of the small square. The side of the large square cuts two sides of the small square into one- third parts and two-thirds parts. What is the area where the squares overlap?

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