Principles of Statistical Analysis: Learning from Randomized Experiments

Ery Arias-Castro

ISBN 10: 1108747442 / ISBN 13: 9781108747448

Edité par Cambridge University Press, 2022

A propos de cet article

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N° de réf. du vendeur MA 9781108747448

Détails bibliographiques

• Titre: Principles of Statistical Analysis: Learning from Randomized Experiments
• Éditeur: Cambridge University Press
• Date de parution: 2022
• Langue: anglais
• ISBN à 10 chiffres: 1108747442
• ISBN à 13 chiffres: 9781108747448
• Reliure: Paperback
• État de l'article: New

A propos de ce titre

Synopsis

This compact course is written for the mathematically literate reader who wants to learn to analyze data in a principled fashion. The language of mathematics enables clear exposition that can go quite deep, quite quickly, and naturally supports an axiomatic and inductive approach to data analysis. Starting with a good grounding in probability, the reader moves to statistical inference via topics of great practical importance – simulation and sampling, as well as experimental design and data collection – that are typically displaced from introductory accounts. The core of the book then covers both standard methods and such advanced topics as multiple testing, meta-analysis, and causal inference.

À propos de l?auteur

Ery Arias-Castro is a professor in the Department of Mathematics and in the Halıcıoğlu Data Science Institute at the University of California, San Diego, where he specializes in theoretical statistics and machine learning. His education includes a bachelor's degree in mathematics and a master's degree in artificial intelligence, both from École Normale Supérieure de Cachan (now École Normale Supérieure Paris-Saclay) in France, as well as a Ph.D. in statistics from Stanford University in the United States.