Residual Plots and Outliers

Residual plots and outliers play pivotal roles in statistical analysis, offering valuable insights into the validity of regression models and the presence of influential data points. Residual plots visualize the discrepancies between observed and predicted values, aiding in the assessment of model adequacy and identifying patterns in the residuals. Meanwhile, outliers, as data points deviating significantly from the overall pattern, can exert undue influence on regression parameters and undermine the model's predictive accuracy. Understanding these concepts is essential for ensuring the robustness and reliability of statistical analyses, making residual plots and outliers crucial components of data exploration and model validation processes.