The purpose of this brief paper is to provide a description of the methods by which researchers attempt to test whether one variable can be said to be related to another. It is not intended in any way to be a substitute for training in statistical methodology. It will, however, provide those without such training some guidelines as to which statistical processes are used in specific situations.

Apologies here to anyone who is trained in Statistics and/or Research Methodology.  Largely avoided here, except in a few footnotes, are the critical mathematical processes for deriving the mentioned statistics.  There is also no real notion of hypotheses or the formal process of hypothesis testing, Type I or II Errors, or descriptive inferences. Given the intended audience, the necessity for brevity, and that the paper is part of a series on the determination of ‘cause-and-effect,’ univariate tests have been skipped. And the biggest faux pas was intentional; there was only tangential mention of the Null Hypothesis.  Better a little, slightly incorrect, understanding than none at all.

Keywords: concomitant variation, causality, cause and effect, statistical relationships


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