In statistics, the coefficient of determination, denoted R2 or r2 and pronounced "R squared", is the proportion of the variation in the dependent variable that is predictable from the independent variable …

Dec 6, 2025 · coefficient of determination, in statistics, R2 (or r2), a measure that assesses the ability of a model to predict or explain an outcome in the linear regression setting.

If r2 = 0, the estimated regression line is perfectly horizontal. The predictor x accounts for none of the variation in y! We've learned the interpretation for the two easy cases — when r2 = 0 or r2 = 1 — but, …

Oct 2, 2025 · R-squared (R 2) is defined as a number that tells you how well the independent variable (s) in a statistical model explains the variation in the dependent variable. It ranges from 0 to 1,...

The R-squared (R 2 R2) value, often called the Coefficient of Determination, is a metric used in regression analysis. But what does that number actually tell you about your regression model?

It is a goodness-of-fit measure that evaluates how closely the model’s predicted values match the actual data. A higher value means the model accounts for more of the outcome’s variability. The coefficient …

Jul 23, 2025 · R-squared, also known as the coefficient of determination, is a statistical measure that represents the proportion of the variance for a dependent variable that's explained by one or more …

Apr 22, 2022 · What is the coefficient of determination? The coefficient of determination (R ²) measures how well a statistical model predicts an outcome. The outcome is represented by the model’s …

What is the Adjusted Coefficient of Determination? The coefficient of determination, R 2, is used to analyze how differences in one variable can be explained by a difference in a second variable. For …

R Squared formula, also known as the coefficient of determination, is generally represented by R2 or r2, giving the number indicating the variance in the dependent variable that is to be predicted from the …