The determination coefficient R² is a measure of the part of the variability explained by the statistical model. There is no consensus about the exact definition of R2. Only in the case of linear regression are all definitions equivalent. In case of single linear regression, R² is simply equal to the square of a correlation coefficient. In the case of linear regression, R² can be defined as the proportion declared variance of the regression model. Interpretation
R2 is a size that provides information about the extent to which a model approximates the actual data. If all predicted values match the actual values then R² = 1. Note that a (perfect) connection does not say anything about the causality in the data.
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