CORRELATION and REGRESSION
It is computed as the regression sum of squares divided by the total (corrected) sum of squares. Values near 0 imply that the regression model has done little to “explain” variation in Y, while values near 1 imply that the model has “explained” a large portion of the variation in Y. If … ................
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