Representativeness in Statistics, Politics, and Machine Learning

This course explores the concept of representativeness in statistics, politics, and machine learning. The learning outcomes include understanding the importance of representativeness in various fields and recognizing normative tensions that may arise. The course covers topics such as statistical roots, representation in science, and crop reporting. The teaching method involves lectures and discussions. This course is intended for researchers, practitioners, and individuals interested in the intersection of statistics, politics, and machine learning.