Goodness of fit is a statistical measure that assesses how well a model's predictions align with the actual data points. It evaluates the extent to which the chosen model captures the underlying patterns in the data, providing insight into the model's accuracy and reliability. In this context, it plays a crucial role in determining the effectiveness of linear regression models through metrics such as R-squared and Adjusted R-squared, which quantify how much of the variability in the dependent variable can be explained by the independent variables.
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