Larry A. Wasserman is a Canadian statistician and professor. His work focuses on statistics and machine learning. Wasserman's writings often explore the theoretical foundations and methodological innovations within these fields. His contributions to the discipline are recognized by both academics and practitioners.
"All of Statistics" offers a comprehensive overview of probability and statistics, ideal for graduate and advanced undergraduate students in related fields. It covers modern topics like non-parametric curve estimation and bootstrapping, requiring knowledge of calculus and basic linear algebra but no prior statistics experience.
Focusing on nonparametric inference, this text offers clear accounts of various contemporary issues in the field. It blends methodology with theoretical insights, making complex concepts accessible. Readers will find a comprehensive resource that effectively balances practical applications with foundational principles, catering to both practitioners and researchers in statistics.