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ISBN10: 1119186846, ISBN13: 9781119186847, [publisher: Wiley] Softcover Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less 0.55 [AUSTELL, GA, U.S.A.] [Publication Year: 2016]
Wiley, Date: 2016. Paperback. Good. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.Dust jacket quality is not guaranteed. 2016. Wiley ISBN 1119186846 9781119186847 [US]
ISBN10: 1119186846, ISBN13: 9781119186847, [publisher: Wiley] Softcover Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages. [Berlin, Germany] [Publication Year: 2016]
Pearl, Judea, Glymour, Madelyn, Jewell, Nicholas P.
USD
34.50
SecondSale /Abebooks
ISBN10: 1119186846, ISBN13: 9781119186847, [publisher: Wiley] Softcover Item in good condition. Textbooks may not include supplemental items i.e. CDs, access codes etc. [Montgomery, IL, U.S.A.] [Publication Year: 2016]
ISBN10: 1119186846, ISBN13: 9781119186847, [publisher: John Wiley & Sons] Softcover Judea Pearl is Professor of Computer cience and Statistics at the University of California, Los Angeles, where he directs the Cognitive Systems Laboratory and conducts research in arti- ficial intelligence, causal inference and philosophy of science. He is . [Greven, Germany] [Publication Year: 2016]
ISBN10: 1119186846, ISBN13: 9781119186847, [publisher: John Wiley & Sons Inc, New York] Softcover Paperback. CAUSAL INFERENCE IN STATISTICS A Primer Causality is central to the understanding and use of data. Without an understanding of causeeffect relationships, we cannot use data to answer questions as basic as "Does this treatment harm or help patients?" But though hundreds of introductory texts are available on statistical methods of data analysis, until now, no beginner-level book has been written about the exploding arsenal of methods that can tease causal information from data. Causal Inference in Statistics fills that gap. Using simple examples and plain language, the book lays out how to define causal parameters; the assumptions necessary to estimate causal parameters in a variety of situations; how to express those assumptions mathematically; whether those assumptions have testable implications; how to predict the effects of interventions; and how to reason counterfactually. These are the foundational tools that any student of statistics needs to acquire in order to use statistical methods to answer causal questions of interest. This book is accessible to anyone with an interest in interpreting data, from undergraduates, professors, researchers, or to the interested layperson. Examples are drawn from a wide variety of fields, including medicine, public policy, and law; a brief introduction to probability and statistics is provided for the uninit ...
ISBN10: 1119186846, ISBN13: 9781119186847, [publisher: Wiley] Softcover Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages. [Berlin, Germany] [Publication Year: 2016]
ISBN10: 1119186846, ISBN13: 9781119186847, [publisher: John Wiley & Sons Inc, New York] Softcover Paperback. CAUSAL INFERENCE IN STATISTICS A Primer Causality is central to the understanding and use of data. Without an understanding of causeeffect relationships, we cannot use data to answer questions as basic as "Does this treatment harm or help patients?" But though hundreds of introductory texts are available on statistical methods of data analysis, until now, no beginner-level book has been written about the exploding arsenal of methods that can tease causal information from data. Causal Inference in Statistics fills that gap. Using simple examples and plain language, the book lays out how to define causal parameters; the assumptions necessary to estimate causal parameters in a variety of situations; how to express those assumptions mathematically; whether those assumptions have testable implications; how to predict the effects of interventions; and how to reason counterfactually. These are the foundational tools that any student of statistics needs to acquire in order to use statistical methods to answer causal questions of interest. This book is accessible to anyone with an interest in interpreting data, from undergraduates, professors, researchers, or to the interested layperson. Examples are drawn from a wide variety of fields, including medicine, public policy, and law; a brief introduction to probability and statistics is provided for the uninit ...
Pearl, Judea; Glymour, Madelyn; Jewell, Nicholas P.
USD
40.33
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ISBN10: 1119186846, ISBN13: 9781119186847, [publisher: Wiley] Softcover Buy with confidence! Book is in good condition with minor wear to the pages, binding, and minor marks within 0.58 [Amherst, NY, U.S.A.] [Publication Year: 2016]
ISBN10: 1119186846, ISBN13: 9781119186847, [publisher: John Wiley & Sons] Softcover Judea Pearl is Professor of Computer cience and Statistics at the University of California, Los Angeles, where he directs the Cognitive Systems Laboratory and conducts research in arti- ficial intelligence, causal inference and philosophy of science. He is . [Greven, Germany] [Publication Year: 2016]
ISBN10: 1119186846, ISBN13: 9781119186847, [publisher: Wiley-Blackwell] Softcover New Book. Shipped from UK. Established seller since 2000. [Fairford, GLOS, United Kingdom] [Publication Year: 2016]
ISBN10: 1119186846, ISBN13: 9781119186847, [publisher: John Wiley & Sons Inc, New York] Softcover Paperback. CAUSAL INFERENCE IN STATISTICS A Primer Causality is central to the understanding and use of data. Without an understanding of causeeffect relationships, we cannot use data to answer questions as basic as "Does this treatment harm or help patients?" But though hundreds of introductory texts are available on statistical methods of data analysis, until now, no beginner-level book has been written about the exploding arsenal of methods that can tease causal information from data. Causal Inference in Statistics fills that gap. Using simple examples and plain language, the book lays out how to define causal parameters; the assumptions necessary to estimate causal parameters in a variety of situations; how to express those assumptions mathematically; whether those assumptions have testable implications; how to predict the effects of interventions; and how to reason counterfactually. These are the foundational tools that any student of statistics needs to acquire in order to use statistical methods to answer causal questions of interest. This book is accessible to anyone with an interest in interpreting data, from undergraduates, professors, researchers, or to the interested layperson. Examples are drawn from a wide variety of fields, including medicine, public policy, and law; a brief introduction to probability and statistics is provided for the uninit ...
Paperback / softback. New. Many of the concepts and terminology surrounding modern causal inference can be quite intimidating to the novice. Judea Pearl presents a book ideal for beginners in statistics, providing a comprehensive introduction to the field of causality. ISBN 1119186846 9781119186847 [GB]
ISBN10: 1119186846, ISBN13: 9781119186847, [publisher: John Wiley & Sons Inc Mär 2016] Softcover Neuware - Many of the concepts and terminology surrounding modern causal inference can be quite intimidating to the novice. Judea Pearl presents a book ideal for beginners in statistics, providing a comprehensive introduction to the field of causality. Examples from classical statistics are presented throughout to demonstrate the need for causality in resolving decision-making dilemmas posed by data. Causal methods are also compared to traditional statistical methods, whilst questions are provided at the end of each section to aid student learning. [Einbeck, Germany] [Publication Year: 2016]
Jewell Nicholas P. University of California Berkeley USA
USD
45.01
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Paperback / softback. New. New Book; Fast Shipping from UK; Not signed; Not First Edition; Many of the concepts and terminology surrounding modern causal inference can be quite intimidating to the novice. Judea Pearl presents a book ideal for beginners in statistics, providing a comprehensive introduction to the field of caus ISBN 1119186846 9781119186847 [GB]
ISBN10: 1119186846, ISBN13: 9781119186847, [publisher: John Wiley and Sons Ltd] Softcover New copy - Usually dispatched within 4 working days. Many of the concepts and terminology surrounding modern causal inference can be quite intimidating to the novice. Judea Pearl presents a book ideal for beginners in statistics, providing a comprehensive introduction to the field of causality. [Southport, United Kingdom] [Publication Year: 2016]
ISBN10: 1119186846, ISBN13: 9781119186847, [publisher: John Wiley & Sons, Limited] Softcover Ships SAME or NEXT business day. We Ship to APO/FPO addr. Choose EXPEDITED shipping and receive in 2-5 business days within the United States. See our member profile for customer support contact info. We have an easy return policy. [Grandview Heights, OH, U.S.A.] [Publication Year: 2016]
Wiley-Blackwell 3/4/2016 12: 00: 00 AM Softcover PLEASE NOTE, WE DO NOT SHIP TO DENMARK. New Book. Shipped from UK in 4 to 14 days. Established seller since 2000. Please note we cannot offer an expedited shipping service from the UK.
ISBN10: 1119186846, ISBN13: 9781119186847, [publisher: John Wiley & Sons Inc Mär 2016] Softcover Neuware - Many of the concepts and terminology surrounding modern causal inference can be quite intimidating to the novice. Judea Pearl presents a book ideal for beginners in statistics, providing a comprehensive introduction to the field of causality. Examples from classical statistics are presented throughout to demonstrate the need for causality in resolving decision-making dilemmas posed by data. Causal methods are also compared to traditional statistical methods, whilst questions are provided at the end of each section to aid student learning. [Einbeck, Germany] [Publication Year: 2016]
Wiley-Blackwell 3/4/2016 12: 00: 00 AM Softcover PLEASE NOTE, WE DO NOT SHIP TO DENMARK. New Book. Shipped from UK in 4 to 14 days. Established seller since 2000. Please note we cannot offer an expedited shipping service from the UK.
ISBN10: 1119186846, ISBN13: 9781119186847, [publisher: John Wiley & Sons Inc] Softcover First Edition Causal Inference in Statistics: A Primer Judea Pearl, Computer Science and Statistics, University of California Los Angeles, USA Madelyn Glymour, Philosophy, Carnegie Mellon University, Pittsburgh, USA and Nicholas P. Num Pages: 150 pages. BIC Classification: PBT. Category: (P) Professional & Vocational. Dimension: 244 x 170. . . 2016. 1st Edition. Paperback. . . . . [Galway, GY, Ireland] [Publication Year: 2016]
Pearl, Judea; Glymour, Madelyn; Jewell, Nicholas P.
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59.00
GoldenWavesOfBooks /Abebooks
ISBN10: 1119186846, ISBN13: 9781119186847, [publisher: Wiley] Softcover New. Fast Shipping and good customer service [Fayetteville, TX, U.S.A.] [Publication Year: 2016]
John Wiley & Sons Inc 2016 Paperback New Causal Inference in Statistics: A Primer Judea Pearl, Computer Science and Statistics, University of California Los Angeles, USA Madelyn Glymour, Philosophy, Carnegie Mellon University, Pittsburgh, USA and Nicholas P. Num Pages: 150 pages. BIC Classification: PBT. Category: (P) Professional & Vocational. Dimension: 244 x 170...2016. 1st Edition. Paperback.....We ship daily from our Bookshop.
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When you click on links to various merchants on this site and make a purchase, this can result in this site earning a commission at no extra cost to you. Affiliate programs and affiliations include, but are not limited to, the eBay Partner Network, Amazon and Alibris.
