Nonstandard terminology warning: the author is using "autocorrelation" in a way I've never seen before. There is a much more common usage of "autocorrelation" to refer to the correlation of a timeseries with itself (shifted by some amount).
If you use autocorrelation to refer to the thing in OP, you'll probably confuse people who know statistics, and vice versa.
> Nonstandard terminology warning: the author is using "autocorrelation" in a way I've never seen before.
That's a nice way of putting it. A more accurate description would be: the author is butchering the key essence of autocorrelation, since they don't clearly mention that it is a temporal relationship!
> What is autocorrelation?
> Autocorrelation occurs when you correlate a variable with itself.
Groan.
A standard definition is:
> Autocorrelation refers to the degree of correlation of the same variables between two successive time intervals. It measures how the lagged version of the value of a variable is related to the original version of it in a time series. Autocorrelation, as a statistical concept, is also known as serial correlation.
The more common experience with autocorrelations are with time series, but what the author said is correct even in that context. A time series autocorrelation relates the same time series function at different times. At the simplest you plot the arrays X vs X where X[i] = f(t[i]). You then may complicate it further by some transformation g(X) vs X (e.g., moving average).
If you use autocorrelation to refer to the thing in OP, you'll probably confuse people who know statistics, and vice versa.