Causality


Author: Judea Pearl
Publisher: Cambridge University Press
ISBN: 1139643983
Category: Science
Page: N.A
View: 3030

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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, economics, philosophy, cognitive science, and the health and social sciences. Judea Pearl presents and unifies the probabilistic, manipulative, counterfactual, and structural approaches to causation and devises simple mathematical tools for studying the relationships between causal connections and statistical associations. Cited in more than 2,100 scientific publications, it continues to liberate scientists from the traditional molds of statistical thinking. In this revised edition, Judea Pearl elucidates thorny issues, answers readers' questions, and offers a panoramic view of recent advances in this field of research. Causality will be of interest to students and professionals in a wide variety of fields. Dr Judea Pearl has received the 2011 Rumelhart Prize for his leading research in Artificial Intelligence (AI) and systems from The Cognitive Science Society.

Causal Inference in Statistics

A Primer
Author: Judea Pearl,Madelyn Glymour,Nicholas P. Jewell
Publisher: John Wiley & Sons
ISBN: 1119186854
Category: Mathematics
Page: 160
View: 2292

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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.

Die Ordnung der Zeit


Author: Carlo Rovelli
Publisher: Rowohlt Verlag GmbH
ISBN: 3644000751
Category: Science
Page: 192
View: 7928

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Leben wir in der Zeit oder lebt die Zeit vielleicht nur in uns? Alle theoretischen Physiker von Weltrang, die den großen und kleinen Kräften des Universums nachspüren, beschäftigen sich immer wieder mit der entscheidenden Frage, was Zeit ist. Wenn ihre großen Modelle die Zeit zur Erklärung des Elementaren nicht mehr brauchen, wie kommt es dann, dass sie für unser Leben so wichtig ist? Geht es wirklich ohne sie? Carlo Rovelli gibt in diesem Buch überraschende Antworten. Er nimmt uns mit auf eine Reise durch unsere Vorstellungen der von der Zeit und spürt ihren Regeln und Rätseln nach. Ein großes, packend geschriebenes Lese-Abenteuer, ein würdiger Nachfolger des Welt-Bestsellers "Sieben kurze Lektionen über Physik".

The Oxford Handbook of Causal Reasoning


Author: Michael Waldmann
Publisher: Oxford University Press
ISBN: 0199399557
Category: Psychology
Page: 768
View: 6936

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Causal reasoning is one of our most central cognitive competencies, enabling us to adapt to our world. Causal knowledge allows us to predict future events, or diagnose the causes of observed facts. We plan actions and solve problems using knowledge about cause-effect relations. Although causal reasoning is a component of most of our cognitive functions, it has been neglected in cognitive psychology for many decades. The Oxford Handbook of Causal Reasoning offers a state-of-the-art review of the growing field, and its contribution to the world of cognitive science. The Handbook begins with an introduction of competing theories of causal learning and reasoning. In the next section, it presents research about basic cognitive functions involved in causal cognition, such as perception, categorization, argumentation, decision-making, and induction. The following section examines research on domains that embody causal relations, including intuitive physics, legal and moral reasoning, psychopathology, language, social cognition, and the roles of space and time. The final section presents research from neighboring fields that study developmental, phylogenetic, and cultural differences in causal cognition. The chapters, each written by renowned researchers in their field, fill in the gaps of many cognitive psychology textbooks, emphasizing the crucial role of causal structures in our everyday lives. This Handbook is an essential read for students and researchers of the cognitive sciences, including cognitive, developmental, social, comparative, and cross-cultural psychology; philosophy; methodology; statistics; artificial intelligence; and machine learning.

Medizinische Statistik


Author: Hans J. Trampisch,Jürgen Windeler
Publisher: Springer-Verlag
ISBN: 364256996X
Category: Mathematics
Page: 376
View: 564

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"Statistiken sind merkwürdige Dinge ...", dies wird so mancher Mediziner denken, wenn er sich mit der Biometrie befaßt. Sei es im Rahmen seiner Ausbildung oder im Zuge wissenschaftlicher oder klinischer Studien, Kenntnisse der Statistik und Mathematik sind unentbehrlich für die tägliche Arbeit des Mediziners. Ziel dieses Lehrbuches ist es, den Mediziner systematisch an biometrische Terminologie und Arbeitsmethoden heranzuführen, um ihn schließlich mit den Grundlagen der Wahrscheinlichkeitsrechung vertraut zu machen. Nach der Lektüre dieses Buches hält der Leser ein Werkzeug in den Händen, das ihm bei der Lösung medizinscher Fragestellungen hilft ebenso wie bei der Beschreibung von Ergebnissen wissenschaftlicher Studien und natürlich bei der Doktorarbeit!

Counterfactuals and Causal Inference


Author: Stephen L. Morgan,Christopher Winship
Publisher: Cambridge University Press
ISBN: 1107065070
Category: Mathematics
Page: 524
View: 428

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This new edition aims to convince social scientists to take a counterfactual approach to the core questions of their fields.

Causal Inference for Statistics, Social, and Biomedical Sciences

An Introduction
Author: Guido W. Imbens,Donald B. Rubin
Publisher: Cambridge University Press
ISBN: 1316094391
Category: Mathematics
Page: N.A
View: 1972

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Most questions in social and biomedical sciences are causal in nature: what would happen to individuals, or to groups, if part of their environment were changed? In this groundbreaking text, two world-renowned experts present statistical methods for studying such questions. This book starts with the notion of potential outcomes, each corresponding to the outcome that would be realized if a subject were exposed to a particular treatment or regime. In this approach, causal effects are comparisons of such potential outcomes. The fundamental problem of causal inference is that we can only observe one of the potential outcomes for a particular subject. The authors discuss how randomized experiments allow us to assess causal effects and then turn to observational studies. They lay out the assumptions needed for causal inference and describe the leading analysis methods, including matching, propensity-score methods, and instrumental variables. Many detailed applications are included, with special focus on practical aspects for the empirical researcher.

Causality

Philosophical Theory meets Scientific Practice
Author: Phyllis Illari,Federica Russo
Publisher: OUP Oxford
ISBN: 0191639680
Category: Mathematics
Page: 336
View: 349

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Head hits cause brain damage - but not always. Should we ban sport to protect athletes? Exposure to electromagnetic fields is strongly associated with cancer development - does that mean exposure causes cancer? Should we encourage old fashioned communication instead of mobile phones to reduce cancer rates? According to popular wisdom, the Mediterranean diet keeps you healthy. Is this belief scientifically sound? Should public health bodies encourage consumption of fresh fruit and vegetables? Severe financial constraints on research and public policy, media pressure, and public anxiety make such questions of immense current concern not just to philosophers but to scientists, governments, public bodies, and the general public. In the last decade there has been an explosion of theorizing about causality in philosophy, and also in the sciences. This literature is both fascinating and important, but it is involved and highly technical. This makes it inaccessible to many who would like to use it, philosophers and scientists alike. This book is an introduction to philosophy of causality - one that is highly accessible: to scientists unacquainted with philosophy, to philosophers unacquainted with science, and to anyone else lost in the labyrinth of philosophical theories of causality. It presents key philosophical accounts, concepts and methods, using examples from the sciences to show how to apply philosophical debates to scientific problems.

Statistik in der Epidemiologie psychischer Störungen


Author: Michael Hoefler
Publisher: Springer-Verlag
ISBN: 3642188826
Category: Psychology
Page: 164
View: 1326

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Ursache und Wirkung verstehen Statistik ganz praxisnah - Bedeutung und Interpretation statistischer und epidemiologischer Verfahren in der Erforschung psychischer Störungen - Statistische Ansätze und Methoden einfach und verständlich erklärt - Viele Anwendungsbeispiele aus der klinischen Psychologie und Psychiatrie - Lösungen für konkrete Probleme im Forschungsalltag - Ein wichtiges Vademekum für Statistiker, Mediziner, Psychologen und Psychiater

Probabilistic Graphical Models for Genetics, Genomics, and Postgenomics


Author: Raphaël Mourad
Publisher: OUP Oxford
ISBN: 0191019208
Category: Mathematics
Page: 464
View: 6551

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Nowadays bioinformaticians and geneticists are faced with myriad high-throughput data usually presenting the characteristics of uncertainty, high dimensionality and large complexity. These data will only allow insights into this wealth of so-called 'omics' data if represented by flexible and scalable models, prior to any further analysis. At the interface between statistics and machine learning, probabilistic graphical models (PGMs) represent a powerful formalism to discover complex networks of relations. These models are also amenable to incorporating a priori biological information. Network reconstruction from gene expression data represents perhaps the most emblematic area of research where PGMs have been successfully applied. However these models have also created renewed interest in genetics in the broad sense, in particular regarding association genetics, causality discovery, prediction of outcomes, detection of copy number variations, and epigenetics. This book provides an overview of the applications of PGMs to genetics, genomics and postgenomics to meet this increased interest. A salient feature of bioinformatics, interdisciplinarity, reaches its limit when an intricate cooperation between domain specialists is requested. Currently, few people are specialists in the design of advanced methods using probabilistic graphical models for postgenomics or genetics. This book deciphers such models so that their perceived difficulty no longer hinders their use and focuses on fifteen illustrations showing the mechanisms behind the models. Probabilistic Graphical Models for Genetics, Genomics and Postgenomics covers six main themes: (1) Gene network inference (2) Causality discovery (3) Association genetics (4) Epigenetics (5) Detection of copy number variations (6) Prediction of outcomes from high-dimensional genomic data. Written by leading international experts, this is a collection of the most advanced work at the crossroads of probabilistic graphical models and genetics, genomics, and postgenomics. The self-contained chapters provide an enlightened account of the pros and cons of applying these powerful techniques.

Mechanism and Causality in Biology and Economics


Author: Hsiang-Ke Chao,Szu-Ting Chen,Roberta L. Millstein
Publisher: Springer Science & Business Media
ISBN: 9400724543
Category: Philosophy
Page: 256
View: 9036

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This volume addresses fundamental issues in the philosophy of science in the context of two most intriguing fields: biology and economics. Written by authorities and experts in the philosophy of biology and economics, Mechanism and Causality in Biology and Economics provides a structured study of the concepts of mechanism and causality in these disciplines and draws careful juxtapositions between philosophical apparatus and scientific practice. By exploring the issues that are most salient to the contemporary philosophies of biology and economics and by presenting comparative analyses, the book serves as a platform not only for gaining mutual understanding between scientists and philosophers of the life sciences and those of the social sciences, but also for sharing interdisciplinary research that combines both philosophical concepts in both fields. The book begins by defining the concepts of mechanism and causality in biology and economics, respectively. The second and third parts investigate philosophical perspectives of various causal and mechanistic issues in scientific practice in the two fields. These two sections include chapters on causal issues in the theory of evolution; experiments and scientific discovery; representation of causal relations and mechanism by models in economics. The concluding section presents interdisciplinary studies of various topics concerning extrapolation of life sciences and social sciences, including chapters on the philosophical investigation of conjoining biological and economic analyses with, respectively, demography, medicine and sociology.

Analysis II


Author: Christiane Tretter
Publisher: Springer-Verlag
ISBN: 3034804768
Category: Mathematics
Page: 149
View: 9469

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Das Lehrbuch ist der zweite von zwei einführenden Bänden in die Analysis. Es zeichnet sich dadurch aus, dass alle Themen der Analysis 2 kompakt zusammengefasst sind und dennoch auf typische Schwierigkeiten eingegangen wird. Beginnend mit der Topologie metrischer Räume über die Differentialrechnung von Funktionen mehrerer reeller Variablen bis zu gewöhnlichen Differentialgleichungen und Fourierreihen, enthält das Buch alle prüfungsrelevanten Inhalte. Der Stoff kann anhand von Beispielen, Gegenbeispielen und Aufgaben nachvollzogen werden.

Rhetorik


Author: Aristoteles,Heinrich Knebel
Publisher: N.A
ISBN: N.A
Category:
Page: 207
View: 1541

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Die Berechnung der Zukunft

Warum die meisten Prognosen falsch sind und manche trotzdem zutreffen - Der New York Times Bestseller
Author: Nate Silver
Publisher: Heyne Verlag
ISBN: 3641112702
Category: Business & Economics
Page: 656
View: 8327

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Zuverlässige Vorhersagen sind doch möglich! Nate Silver ist der heimliche Gewinner der amerikanischen Präsidentschaftswahlen 2012: ein begnadeter Statistiker, als »Prognose-Popstar« und »Wundernerd« weltberühmt geworden. Er hat die Wahlergebnisse aller 50 amerikanischen Bundesstaaten absolut exakt vorausgesagt – doch damit nicht genug: Jetzt zeigt Nate Silver, wie seine Prognosen in Zukunft Terroranschläge, Umweltkatastrophen und Finanzkrisen verhindern sollen. Gelingt ihm die Abschaffung des Zufalls? Warum werden Wettervorhersagen immer besser, während die Terrorattacken vom 11.09.2001 niemand kommen sah? Warum erkennen Ökonomen eine globale Finanzkrise nicht einmal dann, wenn diese bereits begonnen hat? Das Problem ist nicht der Mangel an Informationen, sondern dass wir die verfügbaren Daten nicht richtig deuten. Zuverlässige Prognosen aber würden uns helfen, Zufälle und Ungewissheiten abzuwehren und unser Schicksal selbst zu bestimmen. Nate Silver zeigt, dass und wie das geht. Erstmals wendet er seine Wahrscheinlichkeitsrechnung nicht nur auf Wahlprognosen an, sondern auf die großen Probleme unserer Zeit: die Finanzmärkte, Ratingagenturen, Epidemien, Erdbeben, den Klimawandel, den Terrorismus. In all diesen Fällen gibt es zahlreiche Prognosen von Experten, die er überprüft – und erklärt, warum sie meist falsch sind. Gleichzeitig schildert er, wie es gelingen kann, im Rauschen der Daten die wesentlichen Informationen herauszufiltern. Ein unterhaltsamer und spannender Augenöffner!

Epidemiologic Methods

Studying the Occurrence of Illness
Author: Noel S. Weiss,Thomas D. Koepsell
Publisher: Oxford University Press
ISBN: 0199387788
Category: Medical
Page: 560
View: 4607

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This second edition of Epidemiologic Methods offers a rigorous introduction to the concepts and tools of epidemiologic research. Aimed chiefly at future epidemiologists, the book offers clear descriptions, practical examples, and question/answer sections for each of the science's key concepts. Authored by two award-winning epidemiology instructors, this book is ideally suited for use as a text in a graduate-level course sequence in epidemiologic methods. The book's chapters are organized around three main themes: general concepts and tools of epidemiology; major study designs; and special topics, including screening, outbreak investigations, and use of epidemiology to evaluate policies and programs. With additional exercises at the end of each chapter and expanded attention to topics such as confounding, this new edition of Epidemiologic Methods is an indispensable resource for the next generation of epidemiologic study.

Bias and Causation

Models and Judgment for Valid Comparisons
Author: Dr. Herbert I. Weisberg
Publisher: John Wiley & Sons
ISBN: 9781118058206
Category: Mathematics
Page: 348
View: 8914

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A one-of-a-kind resource on identifying and dealing with bias in statistical research on causal effects Do cell phones cause cancer? Can a new curriculum increase student achievement? Determining what the real causes of such problems are, and how powerful their effects may be, are central issues in research across various fields of study. Some researchers are highly skeptical of drawing causal conclusions except in tightly controlled randomized experiments, while others discount the threats posed by different sources of bias, even in less rigorous observational studies. Bias and Causation presents a complete treatment of the subject, organizing and clarifying the diverse types of biases into a conceptual framework. The book treats various sources of bias in comparative studies—both randomized and observational—and offers guidance on how they should be addressed by researchers. Utilizing a relatively simple mathematical approach, the author develops a theory of bias that outlines the essential nature of the problem and identifies the various sources of bias that are encountered in modern research. The book begins with an introduction to the study of causal inference and the related concepts and terminology. Next, an overview is provided of the methodological issues at the core of the difficulties posed by bias. Subsequent chapters explain the concepts of selection bias, confounding, intermediate causal factors, and information bias along with the distortion of a causal effect that can result when the exposure and/or the outcome is measured with error. The book concludes with a new classification of twenty general sources of bias and practical advice on how mathematical modeling and expert judgment can be combined to achieve the most credible causal conclusions. Throughout the book, examples from the fields of medicine, public policy, and education are incorporated into the presentation of various topics. In addition, six detailed case studies illustrate concrete examples of the significance of biases in everyday research. Requiring only a basic understanding of statistics and probability theory, Bias and Causation is an excellent supplement for courses on research methods and applied statistics at the upper-undergraduate and graduate level. It is also a valuable reference for practicing researchers and methodologists in various fields of study who work with statistical data. This book was selected as the 2011 Ziegel Prize Winner in Technometrics for the best book reviewed by the journal. It is also the winner of the 2010 PROSE Award for Mathematics from The American Publishers Awards for Professional and Scholarly Excellence