Chapter 7
7.20
It is usually said that ‘big data equals big trouble’ where
some ‘pitfalls’ do exist and can occur when analysing data,
especially at the speed of thought. Let’s identify three of the
most common data misinterpretation risks and shed some
light on how they can be avoided:
1.
Correlation mistaken for causation:
It is the
tendency of data analysts to mix the cause of a
phenomenon with its correlation. When two actions
occurred together, one caused the other. This is not
accurate as actions can occur together. The remedy is
to attempt to eliminate the variable you believe to be
causing the phenomenon.
2.
Confirmation ...
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