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Correlations The correlation coefficient is the standard measure of association between two variables. It is used to measure the strength of linear association between two variables. One example of its use is the study of the relationship between height and weight of individuals in a population, and another is finding out how closely related systolic blood pressure and serum cholesterol are. The definition of the sample correlation coefficient is r=sxy/(sx*sy), where sxy is the covariance between two variables, and sx and sy are the standard deviations. Use a separate row for each observation. Values should be separated by spaces or tabs. You can copy data from another program, like a spreadsheet, and paste it into the window above. It may come in as tab-delimited text, but this will not be a problem. Add a first line with variables followed by a list of variable names if you wish variable names to be included in the results. If no variable names are given, var1, var2, and so on are shown. The form is preloaded with the Cherry Tree data. Black Cerry tree data, from Ryan, Joiner and Ryan (1985). For a set of 31 trees, three measurements are given: diameter (inches), height (feet), and volume (cubic feet).
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