A first course in causal inference /

A first course in causal inference /

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Bibliographic Details
Author / Creator:	Ding, Peng (Statistician), author.
Edition:	First edition.
Imprint:	Boca Raton : CRC Press, Taylor & Francis Group, 2024. ©2024
Description:	xxvi, 421 pages : illustrations ; 27 cm.
Language:	English
Series:	Chapman & Hall/CRC texts in statistical science series Texts in statistical science.
Subject:	Mathematical statistics -- Textbooks. Probabilities -- Textbooks. Causation -- Mathematical models. Inference -- Mathematical models.
Format:	Print Book
URL for this record:	http://pi.lib.uchicago.edu/1001/cat/bib/13474164

Hidden Bibliographic Details
ISBN:	9781032758626 1032758627 9781032776316 1032776315 9781003484080
Notes:	Includes bibliographical references and index.
Summary:	"The past decade has witnessed an explosion of interest in research and education in causal inference, due to its wide applications in biomedical research, social sciences, artificial intelligence etc. This textbook, based on the author's course on causal inference at UC Berkeley taught over the past seven years, only requires basic knowledge of probability theory, statistical inference, and linear and logistic regressions. It assumes minimal knowledge of causal inference, and reviews basic probability and statistics in the appendix. It covers causal inference from a statistical perspective and includes examples and applications from biostatistics and econometrics. It would be suitable for an advanced undergraduate or graduate-level course on causal inference, or postgraduate and PhD-level course in statistics and biostatistics departments"--
Other form:	Online version: Ding, Peng (Statistician). First course in causal inference First edition. Boca Raton, FL : CRC Press, 2024 9781003484080

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Call Number:	QA276 .D536 2024
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