st be concerning the manner in which the variables are combined in their effect on the dependent variable in the equation.
Correlation analysis is quite similar to regression analysis in that both procedures are based upon least squares calculations. In one way, however, correlation analysis goes beyond regression analysis by providing a single number that summarizes and expresses the strength the relationship between two variables. Correlation coefficients range from 0.0, which is an indication of no correlation whatever, to 1.0, which is an indication of a perfect correlation. In almost all cases, the correlation coefficient will be more than 0.0 and less than 1.0. As has been stated, the correlation coefficient represents the strength of a relationship between variables. An r of 0.25 (a simple coefficient of correlation is represented by the symbol r, while a multiple coefficient of correlati
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