As we've covered for some time now, correlation is a measure of how strongly two variables fluctuate together. *Autocorrelation* is a measure of how strongly a series correlates to *lagged* versions of itself. A series with strong autocorrelation is said to be **serially correlated**.

Let's take `{8, 6, 7, 5, 3, 0, 9}` to be our example series. This series lagged one observation is `{NA, 8, 6, 7, 5, 3, 0}`:

Lag 0 8 6 7 5 3 0 9Lag 1 NA 8 6 7 5 3 0Lag 2 NA NA 8 6 7 5 3

If we take the correlation coefficient of the lag 0 (observed values) and lag 1, we get -0.06. We can repeat this correlation evaluation for all lags *n-1*, where *n* is the length of the original series. This is the series **autocorrelation function**, or **ACF**.

You can visualize ...