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What is the difference between experimental and correlational research designs?

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Correlation should not be confused with causation: correlation often reveals two factors that vary together, because both of them are effects of a third cause.

In a causal relationship, one variable causes the other. Correlation instead is the association between two variables, which does not necessarily imply causation between them.

Experimental designs are aimed at spotting a causal relationship between two variables by isolating them from other (control) variables (factors which may alter the results). Correlation designs often are preliminary and less expensive studies which do not yet neutralize control variables, but find that one factor is correlated with another one, meaning that we find these two things together more often than we usually would.

We need to find a correlation before we have a causal connection. A statistical generalization is needed in order to establish a correlation, which requires an adequately large sample. Examples can be assessing if there is correlation...

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