Learn essential techniques for improving linear model fit through diagnostic analysis. Explore Ordinary Least Squares (OLS) regression on Anscombe data, conduct residual analysis, and interpret various residual plots. Master the use of Normal Q-Q plots to check for error normality, detect non-uniform error variance, and identify outliers in datasets. Apply these skills to real-world examples, including US Bonds data, and understand how to refine models by removing outliers for more accurate results.
Diagnostics to Improve Linear Model Fit - OLS Analysis and Residual Plots
Overview
Syllabus
Intro
OLS on Anscombe data
OLS: Residual Analysis
OLS: Residual Plots of Anscombe data
Normal Q-Q Plot
OLS: Checking for normality of errors
OLS: Checking for non-uniform error variance
OLS: Checking for outliers in data
OLS: Example for outlier detection
Residual plot for US Bonds data
OLS on US bonds example after removing outliers
Taught by
NPTEL-NOC IITM
