MCDMRegression evaluation

R-squared (R²)

The coefficient of determination, denoted R², measures the proportion of variance in the dependent variable explained by the independent variables in a regression model. Introduced by Karl Pearson in the late 19th century, R² is one of the most widely used metrics for assessing how well a model fits observed data.

Open in MethodMindSoonVideoSoon

Read the full method

Members only

Sign in with a free account to read this section.

Sign in

Sources

  1. Pearson, K. (1896). Mathematical contributions to the theory of evolution. Philosophical Transactions of the Royal Society A, 187, 253-318. DOI: 10.1098/rsta.1896.0007
  2. Pearson, K. (1901). On lines and planes of closest fit to systems of points in space. The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science, 2(11), 559-572. DOI: 10.1080/14786440109462720
  3. Fisher, R. A. (1922). On the mathematical foundations of theoretical statistics. Philosophical Transactions of the Royal Society A, 222, 309-368. DOI: 10.1098/rsta.1922.0009

Related methods

Referenced by

ScholarGateR-squared (Coefficient of Determination). Retrieved 2026-06-04 from https://scholargate.app/en/model-evaluation/r-squared