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Idioma: Inglés
Publicado por Taylor and Francis Ltd, GB, 2024
ISBN 10: 1032758627 ISBN 13: 9781032758626
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Añadir al carritoHardback. Condición: New. 1st. 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.Key Features:All R code and data sets available at Harvard Dataverse.Solutions manual available for instructors upon request from the author.Includes over 100 exercises.This book is suitable for an advanced undergraduate or graduate-level course on causal inference, or postgraduate and PhD-level course in statistics and biostatistics departments.
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Idioma: Inglés
Publicado por Taylor and Francis Ltd, GB, 2024
ISBN 10: 1032758627 ISBN 13: 9781032758626
Librería: Rarewaves.com USA, London, LONDO, Reino Unido
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Añadir al carritoHardback. Condición: New. 1st. 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.Key Features:All R code and data sets available at Harvard Dataverse.Solutions manual available for instructors upon request from the author.Includes over 100 exercises.This book is suitable for an advanced undergraduate or graduate-level course on causal inference, or postgraduate and PhD-level course in statistics and biostatistics departments.
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Añadir al carritoHardcover. Condición: Brand New. 448 pages. 10.25x7.25x1.25 inches. In Stock.
Idioma: Inglés
Publicado por Taylor and Francis Ltd, GB, 2024
ISBN 10: 1032758627 ISBN 13: 9781032758626
Librería: Rarewaves USA United, OSWEGO, IL, Estados Unidos de America
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Añadir al carritoHardback. Condición: New. 1st. 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.Key Features:All R code and data sets available at Harvard Dataverse.Solutions manual available for instructors upon request from the author.Includes over 100 exercises.This book is suitable for an advanced undergraduate or graduate-level course on causal inference, or postgraduate and PhD-level course in statistics and biostatistics departments.
Idioma: Inglés
Publicado por Taylor and Francis Ltd, GB, 2024
ISBN 10: 1032758627 ISBN 13: 9781032758626
Librería: Rarewaves.com UK, London, Reino Unido
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Añadir al carritoHardback. Condición: New. 1st. 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.Key Features:All R code and data sets available at Harvard Dataverse.Solutions manual available for instructors upon request from the author.Includes over 100 exercises.This book is suitable for an advanced undergraduate or graduate-level course on causal inference, or postgraduate and PhD-level course in statistics and biostatistics departments.
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Peng Ding is an Associate Professor in the Department of Statistics at UC Berkeley. His research focuses on causal inference and its applications.The past decade has witnessed an explosion of interest in research and education in causal.
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Añadir al carritoBuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.Key Features:All R code and data sets available at Harvard Dataverse.Solutions manual available for instructors upon request from the author.Includes over 100 exercises.This book is suitable for an advanced undergraduate or graduate-level course on causal inference, or postgraduate and PhD-level course in statistics and biostatistics departments.