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This, however, is easier in theory than in practice, and statisticians have developed various techniques to help differentiate between causation, a variable directly related to phenomena, and association, a variable who's changes occur concurrently with the phenomena, and could be causal or non-causal.
Every morning around sunrise, the rooster crows. Does the rooster cause the sun to rise? Not likely. But, if we were to track and plot the sunrises and rooster crows every morning for a year, it would be evident that they occur concurrently. This is an association. So, then, does the sunrise cause the rooster to crow? Not necessarily...
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