In simple linear regression (which includes an intercept), r2 is simply the square of the sample correlation coefficient (r), between the observed outcomes and the observed predictor values. …

R-squared is a goodness-of-fit measure for linear regression models. This statistic indicates the percentage of the variance in the dependent variable that the independent variables explain …

Apr 22, 2022 · Graphing your linear regression data usually gives you a good clue as to whether its R2 is high or low. For example, the graphs below show two sets of simulated data: The …

May 14, 2025 · Learn what R-squared means in regression analysis, how to calculate it, and when to use it to evaluate model performance. Compare it to related metrics with examples in R and …

Learn about the R squared of a linear regression and its properties. Discover how it is defined, calculated and interpreted.

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 …

May 14, 2025 · To solidify our understanding of R-squared, let's walk through two practical examples: one using simple linear regression and another involving a multiple regression …

Oct 27, 2025 · When looking at relationships through a correlation or regression analysis, we often use the coefficient of determination as a measure of effect size. This is also referred to …

Let's start our investigation of the coefficient of determination, r2, by looking at two different examples — one example in which the relationship between the response y and the predictor …

It is called R-squared because in a simple regression model it is just the square of the correlation between the dependent and independent variables, which is commonly denoted by “r”.