Conclusion: Sometimes the difference of causality and correlation is important.

1. Causality: Causality (also referred to as causation, or cause and effect) is influence by which one event, process, state, or object (a cause) contributes to the production of another event, process, state, or object (an effect) where the cause is partly responsible for the effect, and the effect is partly dependent on the cause.

1) As of the beginning of June in 2022.

2) Refer to Wikipedia "Causality".

2. Correlation: In statistics, correlation or dependence is any statistical relationship, whether causal or not, between two random variables or bivariate data.

1) As of the beginning of June in 2022.

2) Refer to Wikipedia "Correlation".

Related contents:

1. The video version of this episode: [Note 311] Causality and correlation differ, which is important, isn’t it?