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I am a newbie in time series and I understood negative autocorrelation through this example http://www.pmean.com/09/NegativeAutocorrelation.html

If you are looking at the amount of time a doctor spends with successive patients, if the first patient finished faster than expected, you are more likely to adopt a leisurely approach with the second patient. If the first patient takes longer than expected, you are more likely to rush with the second patient, trying to get back on schedule.

Then, if I am correct... high positive auto-correlation (let's say 0.9)... would be: if the first patient took 5', the next/previous one takes 4' 59''.

Then, what would be an example of low auto-correlation (let's say 0.01)? I can't understand the logic behind it...

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    $\begingroup$ This means that after any value one expects any other value with equal probability. $\endgroup$
    – alexeymosco
    Commented Sep 19, 2019 at 18:11
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    $\begingroup$ A simple way to create a time series with zero autocorrelation is to randomly permute the values of any time series. $\endgroup$
    – whuber ♦
    Commented Sep 19, 2019 at 19:01

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