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  The degree of association between two or more variables, mainly used in the statistical analysis of interval and ratio data. In the general linear model a correlation coefficient measures the goodness-of-fit of a regression line to a scatter of points. Its value ranges from +1.0 through 0.0 to -1.0: a value of (1.0 indicates that all of the points lie on the regression line; a positive value indicates that the line slopes upwards to the right and a negative value indicates the converse (i.e. as the values of one variable increase, those of the other decrease). Usually represented by r, the square of the correlation coefficient (r2) is interpreted as the proportion of the variation in one variable that can be accounted for by the variation in the other. For multiple regression equations, the multiple correlation coefficient is R. (RJJ)

Suggested Reading Johnston, R.J. 1978: Multivariate statistical analysis in geography. London and New York: Longman.



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