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Principles of Statistical Analysis: Learning from Randomized Experiments

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SKU 9781108747448 Categories ,
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This concise course in principled data analysis for the mathematically literate uses survey sampling and designed experiments as a foundation for statistical inference. Covering essentials for advanced undergraduates and selected topics typically taught at the graduate level, ...

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Description

Product ID:9781108747448
Product Form:Paperback / softback
Country of Manufacture:GB
Series:Institute of Mathematical Statistics Textbooks
Title:Principles of Statistical Analysis
Subtitle:Learning from Randomized Experiments
Authors:Author: Ery Arias-Castro
Page Count:400
Subjects:Information theory, Information theory, Research methods: general, Probability and statistics, Mathematical and statistical software, Data capture and analysis, Machine learning, Research methods: general, Probability & statistics, Mathematical & statistical software, Data capture & analysis, Machine learning
Description:Select Guide Rating
This concise course in principled data analysis for the mathematically literate uses survey sampling and designed experiments as a foundation for statistical inference. Covering essentials for advanced undergraduates and selected topics typically taught at the graduate level, its 700 problems - many computational - build understanding and skills.
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.
Imprint Name:Cambridge University Press
Publisher Name:Cambridge University Press
Country of Publication:GB
Publishing Date:2022-08-25