Regression diagnostics

Regression diagnostics are tools and methods used to assess the quality and reliability of a regression model, which predicts one variable based on others. They help identify issues like whether the data fits the model well, if there are outliers (unusual observations that can skew results), and if the assumptions of the model (like linearity and equal variance) are met. By using these diagnostics, analysts can ensure their predictions are robust and trustworthy, leading to more accurate conclusions and decisions based on the data.