This monograph serves as an introduction and detailed overview of some important topics in distribution testing, an area of theoretical computer science which falls under the general umbrella of property testing, and sits at the intersection of computational learning, statistical learning and hypothesis testing, information theory, and the theory of machine learning. Written in a tutorial style, the author provides the reader with a thorough overview, including a historical perspective on work to date. After introducing the reader to distribution testing, the author proceeds to cover...