1 Types of Unusual Observations 1.1 Regression Outliers 1.2 Leverage 1.3 Influential Observations 1.4 Good vs. Bad Leverage 2 Detecting Influential Observations 2.1 Graphic diagnostics 2.1.1 A scatter plot with Confidence Ellipse 2.1.2 Quantile Comparison Plots (QQ-Plot) 188.8.131.52 Rule of Thumb 2.1.3 Added-variable plots 2.2 Numerical diagnostics 2.2.1 Hat Matrix 184.108.40.206 Rule of Thumb 2.2.2 Standardized Residuals 220.127.116.11 Rule of Thumb 2.2.3 Studentized Residuals 2.
1 What are Outliers? 2 Causes for Outliers 3 Types of Outliers 4 Philosophy about Finding Outliers 5 General Rules Figure 0.1: Outliers 4 years ago (Yes, back to 2016), I was asked by a director of data science department from a very famous IT company about outliers. Basically, she asked two questions:
What are outliers? How to detect them? Also in my daily research life, I have encountered noisy data all the time.