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Principles of statistical analysislearning from randomized experiments /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Principles of statistical analysisEry Arias-Castro, University of California, San Diego.
Reminder of title:	learning from randomized experiments /
Author:	Arias-Castro, Ery.
Published:	Cambridge, United Kingdom ;Cambridge University Press,2022.
Description:	xvii, 389 p. :ill., digital ;23 cm.
Notes:	Title from publisher's bibliographic system (viewed on 27 Jul 2022).
Subject:	Mathematical statistics
Online resource:	https://doi.org/10.1017/9781108779197
ISBN:	9781108779197

Principles of statistical analysislearning from randomized experiments /
Arias-Castro, Ery.

Principles of statistical analysislearning from randomized experiments /[electronic resource] :Ery Arias-Castro, University of California, San Diego. - Cambridge, United Kingdom ;Cambridge University Press,2022. - xvii, 389 p. :ill., digital ;23 cm. - Institute of Mathematical Statistics textbooks ;15. - Institute of Mathematical Statistics textbooks ;1.

Title from publisher's bibliographic system (viewed on 27 Jul 2022).

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.

ISBN: 9781108779197Subjects--Topical Terms:

182294
Mathematical statistics

LC Class. No.: QA276.12 / .A75 2022

Dewey Class. No.: 519.5

Principles of statistical analysislearning from randomized experiments /
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500 $a Title from publisher's bibliographic system (viewed on 27 Jul 2022).
520 $a 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.
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