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Correlation Does Not Imply Causation

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Correlation does not imply causation

Almost daily we are in (mainly) news media whose owner has a structure similar to some of the following:
One study claims that the more A, the more B
A study says that those who are to have less B.
A study says that since A is, then B is the other way.
In principle, all these headlines indicate that basically what it says A is causing B to happen, or what is the same, that B is a consequence of A. Normally, when one reads the news, just realizing that so there is a correlation between A and B (come on, a relationship between these two events ), but in principle, without any indication that either one of them, even in this case, we cause the other B. (Oakes, 2012)
The study of the correlation between two variables is one of the issues in question in Statistics. To summarize a bit, the question would be something like the following:
- From certain data from each of these variables one estimates if there is any relationship between them. The one most frequently studied is called linear regression (by which we seek if there is no linear relationship between the variables), but there are many more possible types: quadratic, exponential, logarithmic...
- With these data a function (which, for example, is a straight linear regression) that determines us exactly what the relationship between these variables is calculated.
- The actual correlation between them is studied (ie, how strong is the relationship that we calculated based on the initial data) by a correlation coefficient.
This misinterpretation of the correlation is also found, and too often in supposedly serious scientific studies. There are few studies to find some relationship between two variables in the subjects thrown in the pool thus affirming that one causes the other, when in fact in these studies there is no evidence that this is true (simply no correlation)....

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