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Causality: Models, Reasoning, And Inference
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Written By One Of The Preeminent Researchers In The Field, This Book Provides A Comprehensive Exposition Of Modern Analysis Of Causation. It Shows How Causality Has Grown From A Nebulous Concept Into A Mathematical Theory With Significant Applications In The Fields Of Statistics, Artificial Intelligence, Philosophy, Cognitive Science, And The Health And Social Sciences. Pearl Presents A Unified Account Of The Probabilistic, Manipulative, Counterfactual And Structural Approaches To Causation, And Devises Simple Mathematical Tools For Analyzing The Relationships Between Causal Connections, Statistical Associations, Actions And Observations. The Book Will Open The Way For Including Causal Analysis In The Standard Curriculum Of Statistics, Artifical Intelligence, Business, Epidemiology, Social Science And Economics. Students In These Areas Will Find Natural Models, Simple Identification Procedures, And Precise Mathematical Definitions Of Causal Concepts That Traditional Texts Have Tended To Evade Or Make Unduly Complicated. This Book Will Be Of Interest To Professionals And Students In A Wide Variety Of Fields. Anyone Who Wishes To Elucidate Meaningful Relationships From Data, Predict Effects Of Actions And Policies, Assess Explanations Of Reported Events, Or Form Theories Of Causal Understanding And Causal Speech Will Find This Book Stimulating And Invaluable. Professor Of Computer Science At The Ucla, Judea Pearl Is The Winner Of The 2008 Benjamin Franklin Award In Computers And Cognitive Science.
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This product may contain chemicals known to the State of California to cause cancer, birth defects, or other reproductive harm.
For more information, please visit www.P65Warnings.ca.gov.
- Q: What is the page count of this book? A: This book has four hundred pages. It provides a detailed exploration of causality models and their applications.
- Q: What are the dimensions of this book? A: The book measures seven point five two inches in length, one inch in width, and ten point seven five inches in height. These dimensions make it a standard hardcover size.
- Q: What type of binding does this book have? A: This book is bound in hardcover. This binding adds durability and a professional appearance.
- Q: How can I apply the concepts learned in this book? A: You can apply the concepts by using the mathematical tools for analyzing causal relationships in various fields. This includes statistics, artificial intelligence, and social sciences.
- Q: Is this book suitable for beginners in statistics? A: Yes, this book is suitable for both beginners and advanced readers. It offers simple identification procedures and clear definitions of causal concepts.
- Q: At what level is this book appropriate for readers? A: This book is appropriate for college students and professionals. It is designed for readers in fields such as statistics, cognitive science, and economics.
- Q: How should I store this book to keep it in good condition? A: Store this book in a cool, dry place away from direct sunlight. This will help preserve the quality of the hardcover and the pages.
- Q: Can this book be cleaned if it gets dirty? A: Yes, you can clean the book by gently wiping the cover with a damp cloth. Avoid using harsh chemicals to prevent damage.
- Q: Is there a risk of pages tearing if handled frequently? A: No, the hardcover binding and quality of the pages reduce the risk of tearing. However, handle it gently to maintain its condition.
- Q: What if the book arrives damaged? A: If the book arrives damaged, you should contact the seller for a return or replacement. Most retailers have policies to handle such issues.
- Q: Does this book provide practical examples of causation? A: Yes, the book includes practical examples that illustrate the application of causation models. This aids in understanding complex concepts.
- Q: Is this book beneficial for professionals in health sciences? A: Yes, professionals in health sciences will find this book invaluable. It discusses significant applications of causation in public health and epidemiology.
- Q: How does this book compare to other texts on causation? A: This book is unique in its comprehensive approach and mathematical clarity. It offers a unified account of different causation theories.
- Q: What if I need help understanding the content? A: If you need help, consider joining study groups or discussions online. Engaging with others can enhance your understanding of the material.
- Q: Is there a glossary or index in the book? A: Yes, the book includes an index, which helps locate specific topics or concepts quickly. This is particularly useful for academic study.