Method of multiple hypotheses, Reichardt, Charles S.
Автор: Lehmann, Erich L. Romano, Joseph P. Название: Testing statistical hypotheses ISBN: 1441931783 ISBN-13(EAN): 9781441931788 Издательство: Amazon Internet Рейтинг: Цена: 16981.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The Third Edition of Testing Statistical Hypotheses brings it into consonance with the Second Edition of its companion volume on point estimation (Lehmann and Casella, 1998) to which we shall refer as TPE2. We won't here comment on the long history of the book which is recounted in Lehmann (1997) but shall use this Preface to indicate the principal changes from the 2nd Edition. The present volume is divided into two parts. Part I (Chapters 1-10) treats small-sample theory, while Part II (Chapters 11-15) treats large-sample theory. The preface to the 2nd Edition stated that "the most important omission is an adequate treatment of optimality paralleling that given for estimation in TPE." We shall here remedy this failure by treating the di?cult topic of asymptotic optimality (in Chapter 13) together with the large-sample tools needed for this purpose (in Chapters 11 and 12). Having developed these tools, we use them in Chapter 14 to give a much fuller treatment of tests of goodness of 't than was possible in the 2nd Edition, and in Chapter 15 to provide an introduction to the bootstrap and related techniques. Various large-sample considerations that in the Second Edition were discussed in earlier chapters now have been moved to Chapter 11.
Автор: Herbert Hoijtink; Irene Klugkist; Paul Boelen Название: Bayesian Evaluation of Informative Hypotheses ISBN: 1441918744 ISBN-13(EAN): 9781441918741 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents an alternative to traditional "null hypothesis" testing. It builds on the idea that researchers have more informative research questions than the "nothing is going on" null hypothesis, or the "something is going on" alternative hypothesis.
Автор: Pearce Bradley D. Название: Can a Virus Cause Schizophrenia? / Facts and Hypotheses ISBN: 1402073003 ISBN-13(EAN): 9781402073007 Издательство: Springer Рейтинг: Цена: 22359.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Disentangles the various sub-theories of the viral hypothesis, and lays the groundwork for more focused explorations of the mechanisms by which viruses may cause serious mental illness. This book is a useful resource for psychiatrists, psychologists, neurobiologists, and their students.
Автор: Lehmann Название: Testing Statistical Hypotheses ISBN: 0387988645 ISBN-13(EAN): 9780387988641 Издательство: Springer Рейтинг: Цена: 11878.00 р. Наличие на складе: Поставка под заказ.
Описание: This classic textbook, now available from Springer, summarizes developments in the field of hypotheses testing. Optimality considerations continue to provide the organizing principle. However, they are now tempered by a much stronger emphasis on the robustness properties of the resulting procedures. This book is an essential reference for any graduate student in statistics.
Описание: An overview of the asymptotic theory of optimal nonparametric tests is presented in this book. It covers a wide range of topics: Neyman-Pearson and LeCam's theories of optimal tests, the theories of empirical processes and kernel estimators with extensions of their applications to the asymptotic behavior of tests for distribution functions, densities and curves of the nonparametric models defining the distributions of point processes and diffusions. With many new test statistics developed for smooth curves, the reliance on kernel estimators with bias corrections and the weak convergence of the estimators are useful to prove the asymptotic properties of the tests, extending the coverage to semiparametric models. They include tests built from continuously observed processes and observations with cumulative intervals.
Автор: P. Bauer; G. Hommel; E. Sonnemann Название: Multiple Hypothesenpr?fung / Multiple Hypotheses Testing ISBN: 3540505598 ISBN-13(EAN): 9783540505594 Издательство: Springer Рейтинг: Цена: 12157.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Der vorliegende Band fat die Ergebnisse eines zweitagigen Symposions "Multiple Hypothesenprufung" am 6. und 7. November 1987 in Gerolstein/ Eifel zusammen. Das Problem der multiplen Hypothesenprufung stellt sich immer dann, wenn aufgrund eines statistischen Experimentes mehrere Fragestellungen beantwortet werden sollen. Insbesondere innerhalb biologisch-medizi- nischer Studien sind haufig mehrere Behandlungen, mehrere Zielgroen oder Messungen zu mehreren Zeitpunkten zu beurteilen. In der Vergangenheit wurde dem Problem der Multiplizitat der Fragestel- lungen nicht genugend Beachtung geschenkt. Im deutschsprachigen Raum erschien dieses Thema etwa ab Ende der 70er Jahre vermehrt auf Kongres- sen sowie in Veroffentlichungen, ausgelost durch die Arbeiten von MARCUS, PERITZ und GABRIEL (1976) und HOLM (1979). Besonders durch das Schwerpunkuhema "Simultane Hypothesenprufung" und die gemein- same Publikation der Referate im Rahmen des Biometrischen Seminars im Jahre 1981 in Bad Ischl, Osterreich, wurde die Aufmerksamkeit vieler Biometriker auf neuere Entwicklungen in diesem fur die Anwendung so wichtigen Bereich gelenkt. In der Folge kam es zu einer intensiven For- schungstatigkeit an den verschiedensten Stellen, vorwiegend von Biometr- kern und von Statistikern mit engem Verhaltnis zur Biometrie. Es war daher naheliegend zu versuchen, die in diesem Bereich methodisch tatigen Biometriker und Statistiker zu einem intensiven Meinungsaus- tausch zusammenzubringen. Dabei sollte eine Bestandsaufnahme vorge- nommen und uber die Richtung weiterer Entwicklungen diskutiert werden. Schon wahrend des Symposions wurde von emlgen Teilnehmern der Vor- schlag gemacht, den Tagungsband in englischer Sprache abzufassen, um IV den Ergebnissen international eine groere Verbreitung zu ermoglichen.
Tests whether the analysis of competing hypotheses reduces cognitive bias, and proposes a more effective approach
Reveals that a key element of current training provided to the UK and US intelligence communities (and likely all 5-EYES and several European agencies) does not have a proven ability to mitigate cognitive biases
Demonstrates that judging the credibility of information from human sources means that intelligence analysis faces greater complexity and cognitive strain than non-intelligence analysis
Explains the underlying causes cognitive biases, based on meta-analyses of existing research
Shows that identifying the ideal conditions for intelligence analysis is a more effective way of reducing the risk of cognitive bias than the use of ACH
Recent high-profile intelligence failures – from 9/11 to the 2003 Iraq war – prove that cognitive bias in intelligence analysis can have catastrophic consequences. This book critiques the reliance of Western intelligence agencies on the use of a method for intelligence analysis developed by the CIA in the 1990s, the Analysis of Competing Hypotheses (ACH). The author puts ACH to the test in an experimental setting against two key cognitive biases with unique empirical research facilitated by UK’s Professional Heads of Intelligence Analysis unit at the Cabinet Office, and finds that the theoretical basis of the ACH method is significantly flawed. Combining the insight of a practitioner with over 11 years of experience in intelligence with both philosophical theory and experimental research, the author proposes an alternative approach to mitigating cognitive bias that focuses on creating the optimum environment for analysis, challenging current leading theories.
Tests whether the analysis of competing hypotheses reduces cognitive bias, and proposes a more effective approach
Reveals that a key element of current training provided to the UK and US intelligence communities (and likely all 5-EYES and several European agencies) does not have a proven ability to mitigate cognitive biases
Demonstrates that judging the credibility of information from human sources means that intelligence analysis faces greater complexity and cognitive strain than non-intelligence analysis
Explains the underlying causes cognitive biases, based on meta-analyses of existing research
Shows that identifying the ideal conditions for intelligence analysis is a more effective way of reducing the risk of cognitive bias than the use of ACH
Recent high-profile intelligence failures – from 9/11 to the 2003 Iraq war – prove that cognitive bias in intelligence analysis can have catastrophic consequences. This book critiques the reliance of Western intelligence agencies on the use of a method for intelligence analysis developed by the CIA in the 1990s, the Analysis of Competing Hypotheses (ACH). The author puts ACH to the test in an experimental setting against two key cognitive biases with unique empirical research facilitated by UK’s Professional Heads of Intelligence Analysis unit at the Cabinet Office, and finds that the theoretical basis of the ACH method is significantly flawed. Combining the insight of a practitioner with over 11 years of experience in intelligence with both philosophical theory and experimental research, the author proposes an alternative approach to mitigating cognitive bias that focuses on creating the optimum environment for analysis, challenging current leading theories.
Tests whether the analysis of competing hypotheses reduces cognitive bias, and proposes a more effective approach
Reveals that a key element of current training provided to the UK and US intelligence communities (and likely all 5-EYES and several European agencies) does not have a proven ability to mitigate cognitive biases
Demonstrates that judging the credibility of information from human sources means that intelligence analysis faces greater complexity and cognitive strain than non-intelligence analysis
Explains the underlying causes cognitive biases, based on meta-analyses of existing research
Shows that identifying the ideal conditions for intelligence analysis is a more effective way of reducing the risk of cognitive bias than the use of ACH
Recent high-profile intelligence failures – from 9/11 to the 2003 Iraq war – prove that cognitive bias in intelligence analysis can have catastrophic consequences. This book critiques the reliance of Western intelligence agencies on the use of a method for intelligence analysis developed by the CIA in the 1990s, the Analysis of Competing Hypotheses (ACH). The author puts ACH to the test in an experimental setting against two key cognitive biases with unique empirical research facilitated by UK’s Professional Heads of Intelligence Analysis unit at the Cabinet Office, and finds that the theoretical basis of the ACH method is significantly flawed. Combining the insight of a practitioner with over 11 years of experience in intelligence with both philosophical theory and experimental research, the author proposes an alternative approach to mitigating cognitive bias that focuses on creating the optimum environment for analysis, challenging current leading theories.
Описание: Can your students analyze their own understanding of content?
Academic standards call for increased rigor, but simply raising complexity is not enough. Students must also know how to investigate, experiment, solve problems, and deepen their understanding of the content. They need to be able to apply their learning to authentic, reality-based situations.
Engaging in Cognitively Complex Tasks: Classroom Techniques to Help Students Generate & Test Hypotheses Across Disciplines explores explicit techniques for mastering a crucial strategy of instructional practice: teaching students to generate and test hypotheses. It includes:
Explicit steps for implementation
Recommendations for monitoring if students are able to generate and test hypotheses
Adaptations for students who struggle, have special needs, or excel in learning
Examples and nonexamples from classroom practice
Common mistakes and ways to avoid them
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