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People with bigger feet have higher intelligence, and people with smaller feet have lower intelligence. In other words, foot size is correlated with intelligence.

However, it's clear that if I could have made my feet bigger it would not have made me more intelligent. In other words, in increase in foot size is not a cause of greater intelligence.

That's what 'correlation does not imply causation' means.

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Q: What does correlation does not mean causation mean?
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Correlation alone causation?

Correlation alone cannot be able to complicate causation.


Does correlation always equal causation?

No! Correlation by itself is not sufficient to infer or prove causation.


What does correlation mean in maths?

Correlation is a statistical measure of the linear association between two variables. It is important to remember that correlation does not mean causation and also that the absence of correlation does not mean the two variables are unrelated.


Does Correlation alone complicates causation?

does not prove


What is the relationship between correlation and causation?

correlation implies the cause and effect relationship,, but casuality doesn't imply correlation.


How do correlation and causation differ?

Correlation is when two things are related or have similar properties and they can exist independently. Causation means that one thing made the other thing happen.


What are the disadvantages of a correlation study?

Causation cannot be determined.


What does correlation does not imply causation mean?

It is saying that two occurrences happening in sequence does not have to mean that the first event was the cause of the second event.


What is the difference between causation and correlation?

Correlation is when two things are related or have similar properties. They can exist independently. Causation means that one thing made the other thing happen


Why is the politician's argument not very convincing?

It confuses correlation with causation


What are some relationships that exist between variables?

Causation, correlation...


What are the three conditions necessary for causation between variables?

The three conditions necessary for causation between variables are covariance (relationship between variables), temporal precedence (the cause must precede the effect in time), and elimination of plausible alternative explanations (other possible causes are ruled out).