The correlation coefficient, denoted by r, is a measure of the strength of the straight-line or linear relationship between two variables. The purpose of this article is (1) to introduce the effects the distributions of the two individual variables have on the correlation coefficient interval and (2) to provide a procedure for calculating an adjusted correlation coefficient, whose realised correlation coefficient interval is often shorter than the original one. Among the weaknesses, I have never seen the issue that the correlation coefficient interval is restricted by the individual distributions of the two variables being correlated. As a 15-year practiced consulting statistician, who also teaches statisticians continuing and professional studies for the Database Marketing/Data Mining Industry, I see too often that the weaknesses and warnings are not heeded. The correlation coefficient's weaknesses and warnings of misuse are well documented. ![]() It is one of the most used statistics today, second to the mean. Accordingly, this statistic is over a century old, and is still going strong. The ‘correlation coefficient’ was coined by Karl Pearson in 1896.
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