Correlation and causation are two different terms that are often related to how two variables are related in statistics and data science. While correlation is often mentioned more frequently than causation, it’s important to understand the differences between these two concepts. Correlation refers to the strength and direction of the relationship between two variables, while causation refers to the effect that one variable has on another. It’s important to recognize the differences between these two concepts in order to properly analyze and interpret data.

source update: What are the Differences? – Towards AI


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