Testing statistical hypotheses, Lehmann, Erich L. Romano, Joseph P.
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.
Автор: Hartmann, Florian G Lois, Daniel Название: Hypothesen testen ISBN: 3658104600 ISBN-13(EAN): 9783658104603 Издательство: Неизвестно Рейтинг: Цена: 3722.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Die Sozialwissenschaftler Florian G. Hartmann und Daniel Lois erkl ren in diesem Essential Schritt f r Schritt und auf Nachvollziehbarkeit bedacht, wie im Rahmen einer quantitativen Untersuchung Hypothesen berpr ft werden. Dabei werden methodische und statistische Grundbegriffe besprochen und komplexere Sachverhalte anhand von alltagsnahen Beispielen erl utert. Die Autoren sch pfen bei den Erkl rungen aus ihrer Lehr- und Forschungst tigkeit und ber cksichtigen die Erfahrungen ihres eigenen Studiums.
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.
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: Bradley Efron and Trevor Hastie Название: Computer Age Statistical Inference ISBN: 1107149894 ISBN-13(EAN): 9781107149892 Издательство: Cambridge Academ Рейтинг: Цена: 9029.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.
Описание: This volume contains original and refereed contributions from the tenth AMCTM Conference (http://www.nviim.ru/AMCTM2014) held in St. Petersburg (Russia) in September 2014 on the theme of advanced mathematical and computational tools in metrology and testing.
Автор: J. P. Verma, Abdel–Salam G. Abdel–Salam Название: Testing Statistical Assumptions in Research ISBN: 1119528410 ISBN-13(EAN): 9781119528418 Издательство: Wiley Рейтинг: Цена: 15198.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Comprehensively teaches the basics of testing statistical assumptions in research and the importance in doing so
This book facilitates researchers in checking the assumptions of statistical tests used in their research by focusing on the importance of checking assumptions in using statistical methods, showing them how to check assumptions, and explaining what to do if assumptions are not met.
Testing Statistical Assumptions in Research discusses the concepts of hypothesis testing and statistical errors in detail, as well as the concepts of power, sample size, and effect size. It introduces SPSS functionality and shows how to segregate data, draw random samples, file split, and create variables automatically. It then goes on to cover different assumptions required in survey studies, and the importance of designing surveys in reporting the efficient findings. The book provides various parametric tests and the related assumptions and shows the procedures for testing these assumptions using SPSS software. To motivate readers to use assumptions, it includes many situations where violation of assumptions affects the findings. Assumptions required for different non-parametric tests such as Chi-square, Mann-Whitney, Kruskal Wallis, and Wilcoxon signed-rank test are also discussed. Finally, it looks at assumptions in non-parametric correlations, such as bi-serial correlation, tetrachoric correlation, and phi coefficient.
An excellent reference for graduate students and research scholars of any discipline in testing assumptions of statistical tests before using them in their research study
Shows readers the adverse effect of violating the assumptions on findings by means of various illustrations
Describes different assumptions associated with different statistical tests commonly used by research scholars
Contains examples using SPSS, which helps facilitate readers to understand the procedure involved in testing assumptions
Looks at commonly used assumptions in statistical tests, such as z, t and F tests, ANOVA, correlation, and regression analysis
Testing Statistical Assumptions in Research is a valuable resource for graduate students of any discipline who write thesis or dissertation for empirical studies in their course works, as well as for data analysts.
Автор: Mayo, Deborah G. Название: Statistical inference as severe testing ISBN: 1107054133 ISBN-13(EAN): 9781107054134 Издательство: Cambridge Academ Рейтинг: Цена: 8237.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This eye-opener illuminates controversies surrounding widely used statistical methods across the physical, social, and biological sciences. New solutions to philosophical problems of induction, falsification, science vs. pseudoscience are put to work to let statisticians and reproducibility researchers get beyond hardened conceptual disagreements.
Автор: Mayo Deborah G. Название: Statistical Inference as Severe Testing ISBN: 1107664640 ISBN-13(EAN): 9781107664647 Издательство: Cambridge Academ Рейтинг: Цена: 4118.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This eye-opener illuminates controversies surrounding widely used statistical methods across the physical, social, and biological sciences. New solutions to philosophical problems of induction, falsification, science vs. pseudoscience are put to work to let statisticians and reproducibility researchers get beyond hardened conceptual disagreements.
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