Distribution Testing - Hypothesis Testing from Very Little or Very Private Data

Explore a comprehensive lecture on distribution testing and hypothesis testing techniques for scenarios with limited or highly private data. Delve into advanced statistical methods presented by Clément Canonne from the University of Sydney as part of the Sublinear Algorithms Boot Camp. Gain insights into innovative approaches for analyzing distributions when faced with data scarcity or privacy constraints, and understand how these methods can be applied in various fields of study.

Distribution Testing: Hypothesis Testing from Very Little (or Very Private) Data