Residual Diagnostics Trend 2026

Residual diagnostics assess the difference between observed and predicted values in statistical models. Analysts use plots and tests to check assumptions like normality, independence, and homoscedasticity. This process ensures model reliability, helping data scientists, economists, and researchers validate predictions, avoid biased conclusions, and improve forecasting accuracy across fields like finance and healthcare.