Monthly Archives: March 2016

A common pitfall with correlations in timeseries

Correlations are often considered an important measure to understand the underlying (probably hidden) patterns in data sets. But as with other statistical measures, a complex situation (many variables, many rows of data) is reduced to a simple numeric value which … Continue reading

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