Explore measurement error in statistical analysis through this comprehensive lecture from the Statistical Rethinking 2022 series. Delve into Bertrand's pancake paradox, examine income recall errors, and investigate divorce rate measurements. Learn to code models addressing measurement error, handle errors on predictors, and understand misclassification issues. Discover the challenges posed by floating point monsters in computational statistics. Gain valuable insights into dealing with various forms of measurement error in statistical modeling and analysis.
Statistical Rethinking 2022 - Measurement Error
Overview
Syllabus
Introduction
Bertrand's pancake paradox
Measurement error
Income and recall error
Divorce rates and measurement
Coding the model
Error on predictor
Misclassification
Floating point monsters
Summary and outlook
Taught by
Richard McElreath
