Correlation is at the core of all statistical work, whether it’s economics, data science, machine learning, or geography.

Correlation is the observation of whether two entities have a direct relationship where one affects the other.

As an example: pressing the gas pedal in a car does increase its speed, meaning the pedal correlates to the speed. However, adjusting the mirror does not change the speed as they do not correlate.

Another concept of correlation is causation. Which is the confirmation that event A causes an effect in event B.

You will hear/read the statement “correlation does not imply causation” many times in the context of statistics. It’s a pitfall to assume two numbers increasing together are correlated, as the “causation” has to be investigated as well.