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Author: Samantha Kleinberg
Publisher: Cambridge University Press
Published: 2019-09-26
Total Pages: 273
ISBN-13: 1108476678
DOWNLOAD EBOOKExplores the critical role time plays in our understanding of causality, across psychology, biology, physics and the social sciences.
Author: Samantha Kleinberg
Publisher: Cambridge University Press
Published: 2019-09-26
Total Pages: 273
ISBN-13: 1108756018
DOWNLOAD EBOOKThis book, geared toward academic researchers and graduate students, brings together research on all facets of how time and causality relate across the sciences. Time is fundamental to how we perceive and reason about causes. It lets us immediately rule out the sound of a car crash as its cause. That a cause happens before its effect has been a core, and often unquestioned, part of how we describe causality. Research across disciplines shows that the relationship is much more complex than that. This book explores what that means for both the metaphysics and epistemology of causes - what they are and how we can find them. Across psychology, biology, and the social sciences, common themes emerge, suggesting that time plays a critical role in our understanding. The increasing availability of large time series datasets allows us to ask new questions about causality, necessitating new methods for modeling dynamic systems and incorporating mechanistic information into causal models.
Author: Phyllis McKay Illari
Publisher: Oxford University Press
Published: 2011-03-17
Total Pages: 953
ISBN-13: 0199574138
DOWNLOAD EBOOKWhy do ideas of how mechanisms relate to causality and probability differ so much across the sciences? Can progress in understanding the tools of causal inference in some sciences lead to progress in others? This book tackles these questions and others concerning the use of causality in the sciences.
Author: Judea Pearl
Publisher: Basic Books
Published: 2018-05-15
Total Pages: 432
ISBN-13: 0465097618
DOWNLOAD EBOOKA Turing Award-winning computer scientist and statistician shows how understanding causality has revolutionized science and will revolutionize artificial intelligence "Correlation is not causation." This mantra, chanted by scientists for more than a century, has led to a virtual prohibition on causal talk. Today, that taboo is dead. The causal revolution, instigated by Judea Pearl and his colleagues, has cut through a century of confusion and established causality -- the study of cause and effect -- on a firm scientific basis. His work explains how we can know easy things, like whether it was rain or a sprinkler that made a sidewalk wet; and how to answer hard questions, like whether a drug cured an illness. Pearl's work enables us to know not just whether one thing causes another: it lets us explore the world that is and the worlds that could have been. It shows us the essence of human thought and key to artificial intelligence. Anyone who wants to understand either needs The Book of Why.
Author: Yemima Ben-Menahem
Publisher: Princeton University Press
Published: 2018-06-12
Total Pages: 221
ISBN-13: 1400889294
DOWNLOAD EBOOKThis book explores the role of causal constraints in science, shifting our attention from causal relations between individual events--the focus of most philosophical treatments of causation—to a broad family of concepts and principles generating constraints on possible change. Yemima Ben-Menahem looks at determinism, locality, stability, symmetry principles, conservation laws, and the principle of least action—causal constraints that serve to distinguish events and processes that our best scientific theories mandate or allow from those they rule out. Ben-Menahem's approach reveals that causation is just as relevant to explaining why certain events fail to occur as it is to explaining events that do occur. She investigates the conceptual differences between, and interrelations of, members of the causal family, thereby clarifying problems at the heart of the philosophy of science. Ben-Menahem argues that the distinction between determinism and stability is pertinent to the philosophy of history and the foundations of statistical mechanics, and that the interplay of determinism and locality is crucial for understanding quantum mechanics. Providing historical perspective, she traces the causal constraints of contemporary science to traditional intuitions about causation, and demonstrates how the teleological appearance of some constraints is explained away in current scientific theories such as quantum mechanics. Causation in Science represents a bold challenge to both causal eliminativism and causal reductionism—the notions that causation has no place in science and that higher-level causal claims are reducible to the causal claims of fundamental physics.
Author: Rebecca B. Morton
Publisher: Cambridge University Press
Published: 2010-08-06
Total Pages: 607
ISBN-13: 1139490532
DOWNLOAD EBOOKIncreasingly, political scientists use the term 'experiment' or 'experimental' to describe their empirical research. One of the primary reasons for doing so is the advantage of experiments in establishing causal inferences. In this book, Rebecca B. Morton and Kenneth C. Williams discuss in detail how experiments and experimental reasoning with observational data can help researchers determine causality. They explore how control and random assignment mechanisms work, examining both the Rubin causal model and the formal theory approaches to causality. They also cover general topics in experimentation such as the history of experimentation in political science; internal and external validity of experimental research; types of experiments - field, laboratory, virtual, and survey - and how to choose, recruit, and motivate subjects in experiments. They investigate ethical issues in experimentation, the process of securing approval from institutional review boards for human subject research, and the use of deception in experimentation.
Author: Paul M. Kellstedt
Publisher: Cambridge University Press
Published: 2009
Total Pages: 293
ISBN-13: 052187517X
DOWNLOAD EBOOKThis textbook introduces the scientific study of politics, supplying students with the basic tools to be critical consumers and producers of scholarly research.
Author: Federica Russo
Publisher: Springer Science & Business Media
Published: 2008-09-18
Total Pages: 236
ISBN-13: 1402088175
DOWNLOAD EBOOKThis investigation into causal modelling presents the rationale of causality, i.e. the notion that guides causal reasoning in causal modelling. It is argued that causal models are regimented by a rationale of variation, nor of regularity neither invariance, thus breaking down the dominant Human paradigm. The notion of variation is shown to be embedded in the scheme of reasoning behind various causal models. It is also shown to be latent – yet fundamental – in many philosophical accounts. Moreover, it has significant consequences for methodological issues: the warranty of the causal interpretation of causal models, the levels of causation, the characterisation of mechanisms, and the interpretation of probability. This book offers a novel philosophical and methodological approach to causal reasoning in causal modelling and provides the reader with the tools to be up to date about various issues causality rises in social science.
Author: Judea Pearl
Publisher: John Wiley & Sons
Published: 2016-01-25
Total Pages: 162
ISBN-13: 1119186862
DOWNLOAD EBOOKCAUSAL INFERENCE IN STATISTICS A Primer Causality is central to the understanding and use of data. Without an understanding of cause–effect 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 uninitiated; and each chapter comes with study questions to reinforce the readers understanding.
Author: B.V. Sreekantan
Publisher: Taylor & Francis
Published: 2019-12-06
Total Pages: 178
ISBN-13: 0429534744
DOWNLOAD EBOOKThis book examines issues related to the concepts of space, time and causality in the context of modern physics and ancient Indian traditions. It looks at the similarity and convergence of these concepts of modern physics with those discussed in ancient Indian wisdom. The volume brings the methodologies of empiricism and introspection together to highlight the synergy between these two strands. It discusses wide-ranging themes including the quantum vacuum as ultimate reality, quantum entanglement and metaphysics of relations, identity and individuality, and dark energy and anti-matter as discussed in physics and in Indian philosophical schools like Vedanta, Yoga, Buddhist, Kashmiri Shaivism and Jaina Philosophy. First of its kind, this book will be an essential read for scholars and researches of philosophy, Indian philosophy, philosophy of science, theoretical physics and social science.
