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Causal Inference in Statistics A Primer.

Detalles Bibliográficos
Autor principal: Pearl, Judea
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Newark : John Wiley & Sons, Incorporated, 2016.
Colección:New York Academy of Sciences Ser.
Temas:
Acceso en línea:Texto completo

MARC

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245 1 0 |a Causal Inference in Statistics  |h [electronic resource] :  |b A Primer. 
260 |a Newark :  |b John Wiley & Sons, Incorporated,  |c 2016. 
300 |a 1 online resource (182 p.). 
490 1 |a New York Academy of Sciences Ser. 
500 |a Description based upon print version of record. 
505 0 |a Intro -- Title Page -- Copyright -- Dedication -- Table of Contents -- About the Authors -- Preface -- Acknowledgments -- List of Figures -- About the Companion Website -- Chapter 1: Preliminaries: Statistical and Causal Models -- 1.1 Why Study Causation -- 1.2 Simpson's Paradox -- 1.3 Probability and Statistics -- 1.4 Graphs -- 1.5 Structural Causal Models -- Bibliographical Notes for Chapter 1 -- Chapter 2: Graphical Models and Their Applications -- 2.1 Connecting Models to Data -- 2.2 Chains and Forks -- 2.3 Colliders -- 2.4 d-separation -- 2.5 Model Testing and Causal Search 
505 8 |a Bibliographical Notes for Chapter 2 -- Chapter 3: The Effects of Interventions -- 3.1 Interventions -- 3.2 The Adjustment Formula -- 3.3 The Backdoor Criterion -- 3.4 The Front-Door Criterion -- 3.5 Conditional Interventions and Covariate-Specific Effects -- 3.6 Inverse Probability Weighing -- 3.7 Mediation -- 3.8 Causal Inference in Linear Systems -- Bibliographical Notes for Chapter 3 -- Chapter 4: Counterfactuals and Their Applications -- 4.1 Counterfactuals -- 4.2 Defining and Computing Counterfactuals -- 4.3 Nondeterministic Counterfactuals -- 4.4 Practical Uses of Counterfactuals 
505 8 |a 4.5 Mathematical Tool Kits for Attribution and Mediation -- Bibliographical Notes for Chapter 4 -- References -- Index -- End User License Agreement 
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830 0 |a New York Academy of Sciences Ser. 
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