The intention of a LINEAR CORRELATION ANALYSIS is to resolve whether there is a relationship between two sets of variables. We may find that: 1) there is a positive correlation, 2) there is a negative correlation, or 3) there is no correlation.
We cannot deduce causation from correlation: correlation does not imply causation. The main problem with all correlations is that there are many models consistent with any correlation: the correlation between two variables may be caused by a third, fourth, or dozens of variables other than the two being compared. Therefore we are left with numerous substitute models in addition to the obvious ones.
The error in the conclusion is referred to as attributing Association as Causation. It means the mistaken assumption that because two events occur together, one causes the other. It may be true that cigarette consumption is positively correlated with increase in pulse rate, but there is no evidence to show that cigarette consumption causes such increase.
References;
http://www.radford.edu/~biol-web/stats/correl_explanation.doc http://en.wikipedia.org/wiki/Correlation_function_%28astronomy%29
References: http://www.radford.edu/~biol-web/stats/correl_explanation.doc http://en.wikipedia.org/wiki/Correlation_function_%28astronomy%29
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