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Adelo Vieira (talk | contribs) (→Correlation \neq Causation) |
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| − | 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 | + | 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! https://study.com/academy/lesson/causation-in-statistics-definition-examples.html |
| − | Given any two correlated events A and B, the following | + | Given any two correlated events A and B, the following options are possible: |
* A causes B | * A causes B | ||
* B causes A | * B causes A | ||
| − | * A and B are both the product of a common underlying | + | * A and B are both the product of a common underlying event, 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) | ||
Revision as of 21:06, 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 the value of another variable, it is said that 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! https://study.com/academy/lesson/causation-in-statistics-definition-examples.html
Given any two correlated events A and B, the following options are possible:
- A causes B
- B causes A
- A and B are both the product of a common underlying event, 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?
