Coefficient of determination
（重定向自Squared multiple correlation）
![Ordinary least squares regression of Okun's law. Since the regression line does not miss any of the points by very much, the R2 of the regression is relatively high.](/Images/godic/202502/12/Okuns_law_quarterly_differences.svg4634.png")
![Comparison of the Theil–Sen estimator (black) and simple linear regression (blue) for a set of points with outliers. Because of the many outliers, neither of the regression lines fits the data well, as measured by the fact that neither gives a very high R2.](/Images/godic/202502/12/Thiel-Sen_estimator.svg4634.png")
![](/Images/godic/202502/12/Coefficient_of_Determination.svg4634.png")
In statistics, the coefficient of determination, denoted R or r and pronounced R squared, is a number that indicates the proportion of the variance in the dependent variable that is predictable from the independent variable.
It is a statistic used in the context of statistical models whose main purpose is either the prediction of future outcomes or the testing of hypotheses, on the basis of other related information. It provides a measure of how well observed outcomes are replicated by the model, based on the proportion of total variation of outcomes explained by the model (pp. 187, 287).