Correlation shows a possible relationship between two random variables. It does not say one variable causes a result in another. It further is wrong to conclude if event B occurs after event A, then A caused B. An example from Darrell Huff's book, "How to Lie with Statistics": A correlation is found between smoking and low grades. Does that mean that smoking causes low grades, or low grades cause people to smoke? It seems a good deal more probable that neither of these things produced the other, but that both are a product of some third factor. The inches of rain in Spain may correlate with the temperatures in Mexico, only because there is similarity of seasons. Small or improperly taken sample may show excellent correlations. The cumulative sum of births in China in one year (each day the total is the sum of all other previous days) will show an excellent correlation with the cumulative sum of rainfall in Germany. This correlation is because the the same values are repeated in the cumulative sums.
Chat with our AI personalities
No! Correlation by itself is not sufficient to infer or prove causation.
correlation implies the cause and effect relationship,, but casuality doesn't imply correlation.
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.
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
Causation, correlation...