R-squared, also known as the coefficient of determination, is a measure used to evaluate the performance of a regression model in explaining the variability in a dataset. It represents the percentage of the variation in the data that can be attributed to the independent variables included in the model. In other words, it indicates how well the model fits the data. A higher R-squared value indicates a better fit, while a lower value suggests that the model may not be a good representation of the data. Understanding this concept is crucial in analyzing and interpreting the results of a regression analysis.
