A measure of the extent to which there is a correspondence between the observed values of a Dependent Variable and the predicted values from a Predictive Model. There are two commonly-used and equivalent ways of computing the variance:
- The ratio of the varianceof the predicted values to the variance of the observed values. (This formula only works where the predicted values are, in some sense, optimal.)[note 1]
- The square of the Pearson's Product-Moment Correlation coefficient.
Also known as
- Proportion of variance explained.
- For example, Maximum Likelihood estimates.
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