Imagine that we took measurements from a thermometer on my window and a ridiculously large tuning fork over several years. The first set of data is temperature T over time t, so it looks like a list of data points [(t0, T0), (t1, T1), …]. The second set of data is mechanical strain e in the tuning fork over time, so it looks like a list of data points [(t0, e0), (t1, e1), …]. We line up the temperature and strain data according to time, yielding [(T0, e0), (T1, e1), …] and find a significant correlation between the two, since they happen to have similar periodicity.
Note that unless their frequency is exactly the same, over a long enough time period (compared to the reciprocal of the difference between the frequencies) the correlation will be zero.
(EDIT: OTOH, any two things that vary monotonically with time will correlate. 123 (I think I’ve seen a few more.))
As for the rest of the post, see the Timeless Physics post by EY and the references therein.
Note that unless their frequency is exactly the same, over a long enough time period (compared to the reciprocal of the difference between the frequencies) the correlation will be zero.
(EDIT: OTOH, any two things that vary monotonically with time will correlate. 1 2 3 (I think I’ve seen a few more.))
As for the rest of the post, see the Timeless Physics post by EY and the references therein.