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1. Exploratory Data Analysis
1.3. EDA Techniques
1.3.3. Graphical Techniques: Alphabetic Autocorrelation Plot

Autocorrelation Plot: Random Data

Autocorrelation Plot The following is a sample autocorrelation plot.

An autocorrelation plot which shows no significant auto
 correlations and randomness

Conclusions We can make the following conclusions from this plot.
  1. There are no significant autocorrelations.
  2. The data are random.
Discussion Note that with the exception of lag 0, which is always 1 by definition, almost all of the autocorrelations fall within the 95% confidence limits. In addition, there is no apparent pattern (such as the first twenty-five being positive and the second twenty-five being negative). This is the abscence of a pattern we expect to see if the data are in fact random.

A few lags slightly outside the 95% and 99% confidence limits do not neccessarily indicate non-randomness. For a 95% confidence interval, we might expect about one out of twenty lags to be statistically significant due to random fluctuations.

There is no associative ability to infer from a current value Yi as to what the next value Yi+1 will be. Such non-association is the essense of randomness. In short, adjacent observations do not "co-relate", so we call this the "no autocorrelation" case.

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