Coefficient of determination

As explained in Statistics Slam Dunk

R2, or the coefficient of determination, is the proportion of variation in a response explained by a regression model.

How Statistics Slam Dunk covers it

How deep it goes

Defines R² and adjusted R², interprets output, and stops short of deriving their formulas.

Examples

Uses an NBA wins model, broom output, fitted wins, and an average absolute error of 8.27 wins.

What it assumes

Assumes a fitted regression model with a response and predictors, while defining R² before interpreting it.

What you can do after

Evaluate regression fit with broom’s glance() output and distinguish raw R² from adjusted R².

How it connects

Connects regression models with predictors, adjusted R-squared, p-values, fitted values, and prediction error.

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Also explained in

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  Effective Data AnalysisR2 is the proportion of variation in an outcome explained by a fitted regression model relative to a baseline model.
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  Statistics Every Programmer NeedsThe coefficient of determination, commonly denoted R-squared, is a regression metric measuring the proportion of dependent-variable variance explained by a fitted model.
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  Starting Data Analytics with Generative AI and PythonR2 is the proportion of variance in a dependent variable explained by a regression model's independent variables.
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  Causal Inference for Data ScienceR squared is the coefficient of determination measuring the proportion of outcome variation explained by a model.
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  Machine Learning for Tabular Data: XGBoost, Deep Learning, and AIR-squared is a goodness-of-fit metric measuring the proportion of variance in the target explained by a predictive model.
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  liveBookmanning.com
  Ensemble Methods for Machine LearningThe coefficient of determination, or R² score, is a regression metric measuring the proportion of target variance explained by a model relative to a constant-mean baseline.

Compare how 7 books explain coefficient of determination →

Related concepts

• linear regressionmeasures · Linear regression is a statistical modeling method that estimates a continuous response as a linear combination of predictor variables and fitted coefficients.
• correlationequivalent to · Correlation is a statistical relationship describing how two or more variables or quantities vary together, including the strength and direction of their association, without by itself implying causation.
• goodness-of-fit measuremeasures · A goodness-of-fit measure quantifies how closely a statistical model or representation agrees with observed data or specified relationships.
• adjusted r-squaredincludes · Adjusted R-squared is a regression goodness-of-fit statistic that modifies R-squared to account for the number of predictors and the sample size.

This explainer was generated by Manning's knowledge graph from the text of Statistics Slam Dunk. The section links point to the parts of the book it draws on.