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* A and B are both the product of a common underlying cause, but do not cause each other | * A and B are both the product of a common underlying cause, but do not cause each other | ||
* Any relationship between A and B is simply the result of coincidence (pure chance) | * Any relationship between A and B is simply the result of coincidence (pure chance) | ||
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| + | <br /> | ||
| + | '''Some examples: Causality or coincidence?''' | ||
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| + | <div style="text-align: center;"> | ||
| + | <pdf width="2000" height="600">File:Correlation_examples-Causality_vs_coincidence.pdf</pdf> | ||
| + | [[File:Correlation_examples-Causality_vs_coincidence.pdf]] | ||
| + | </div> | ||
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Revision as of 20:28, 23 December 2020
Correlation Causation
Even if you find the strongest of correlations, you should never interpret it as more than just that... a correlation.
Causation indicates a relationship between two events where one event is affected by the other. In statistics, when the value of one variable, increases or decreases as a result of other events, it is said there is causation.
Let's say you have a job and get paid a certain rate per hour. The more hours you work, the more income you will earn, right? This means there is a relationship between the two events and also that a change in one event (hours worked) causes a change in the other (income). This is causation in action! https://study.com/academy/lesson/causation-in-statistics-definition-examples.html
Given any two correlated events A and B, the following relationships are possible:
- A causes B
- B causes A
- A and B are both the product of a common underlying cause, but do not cause each other
- Any relationship between A and B is simply the result of coincidence (pure chance)
Some examples: Causality or coincidence?
