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Ordinary least squares regression of Okun's law.Since the regression line does not miss any of the points by very much, the R 2 of the regression is relatively high.. In statistics, the coefficient of determination, denoted R 2 or r 2 and pronounced "R squared", is the proportion of the variation in the dependent variable that is predictable from the independent variable(s).
A related effect size is r 2, the coefficient of determination (also referred to as R 2 or "r-squared"), calculated as the square of the Pearson correlation r. In the case of paired data, this is a measure of the proportion of variance shared by the two variables, and varies from 0 to 1.
The square of the sample correlation coefficient is typically denoted r 2 and is a special case of the coefficient of determination. In this case, it estimates the fraction of the variance in Y that is explained by X in a simple linear regression .
The coefficient of determination R 2 is defined as a ratio of "explained" variance to the "total" variance of the dependent variable y, in the cases where the regression sum of squares equals the sum of squares of residuals: [14]
Coefficient of determination (the R-squared measure of goodness of fit); ... This has approximately a chi-square distribution with k − 1 degrees of freedom.
The last value listed, labelled “r2CU” is the pseudo-r-squared by Nagelkerke and is the same as the pseudo-r-squared by Cragg and Uhler. Pseudo-R-squared values are used when the outcome variable is nominal or ordinal such that the coefficient of determination R 2 cannot be applied as a measure for goodness of fit and when a likelihood ...
R 2 or r 2 (pronounced R-squared), the coefficient of determination of a linear regression in statistics; R 2, the two-dimensional real coordinate space in mathematics; R2: Risk of explosion by shock, friction, fire or other sources of ignition, a risk phrase in chemistry
He is well known in epidemiology thanks to his invention of what is now known as the "Nagelkerke R2", which is one of a number of generalisations of the coefficient of determination from linear regression to logistic regression, see Pseudo-R-squared, Coefficient of determination, Logistic regression.