https://www.statology.org/from-correlation-to-causation-deep-dive-into-data-interpretation/
From Correlation to Causation: Deep Dive into Data Interpretation
Correlation and Causation are key concepts in data analysis.
However, correlation doesn't mean causation.
For example, ice cream sales and sunburns increase in the summer.
These events happen together but do not cause each other.
They occur together because of a third factor: hot weather.

In this article, we will learn more about correlation and causation. We will also understand how these terms are different from each other.

Causation vs. Correlation:

"Correlation" does not mean one variable causes the other to change.
It only shows that they change together.

Influence of Outliers: Outliers can change the correlation a lot. They can make the relationship stronger or weaker than it really is. Special methods can help reduce the impact of outliers.

Causation

Causation refers to a cause-and-effect relationship between variableS.
It means that changes in one variable cause changes in another variable.