Data considerations for Cross Correlation

To ensure that your results are valid, consider the following guidelines when you collect data, perform the analysis, and interpret your results.

Record data in chronological order
Time series data are collected at regular intervals and are recorded in time order. You should record the data in the worksheet in the same order that you collect it. If the data are not in chronological order, you cannot assess time-related patterns in the data. However, you can still use Scatterplot to investigate the relationship between a pair of continuous variables.
Collect enough data to assess trends or patterns
Collect enough data so that you can fully assess trends or patterns in the data. For example, you need enough data to be sure that any pattern you observe is a long-term pattern and not just a short-term anomaly.
Collect data at appropriate time intervals
You should have a time interval that lets the effects of one series to translate into effects on the other series. If the time interval between data points is too long, you might not see the effects. If the time interval is too short, the effects could be written off as white noise.
There should be no autocorrelation
To look for evidence of autocorrelation in the two series, examine the cross-correlation function for a large correlation, with the correlations on both sides slowly decreasing to 0. The autocorrelation usually causes difficulty in identifying meaningful relationships between the two time series. If you see evidence of autocorrelation, you should pre-whiten the data. For more information, go to Pre-whitening data for the cross-correlation function.
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