The coefficient of determination (R-squared) is a measure of how well a linear regression model fits a set of data. It represents the proportion of the variatio...
The coefficient of determination (R-squared) is a measure of how well a linear regression model fits a set of data. It represents the proportion of the variation in the dependent variable that is explained by the independent variables in the model.
The R-squared value ranges from 0 to 1, with 0 indicating no relationship between the independent and dependent variables and 1 indicating a perfect fit. A high R-squared value indicates that the model explains a significant portion of the variation in the dependent variable, while a low R-squared value indicates that the model does not explain much of the variation in the dependent variable.
R-squared is often used to compare different regression models and to select the one that best fits the data. It can also be used to assess the overall goodness-of-fit of a regression model