This text is intended to provide a strong theoretical background in testing hypotheses and decision theory for those who will be practicing in the real worldorwhowillbeparticipatinginthet… Mehr…
This text is intended to provide a strong theoretical background in testing hypotheses and decision theory for those who will be practicing in the real worldorwhowillbeparticipatinginthetrainingofreal-worldstatisticiansand biostatisticians. In previous editions of this text, my rhetoric was somewhat tentative. I was saying, in e?ect, “Gee guys, permutation methods provide a practical real-world alternative to asymptotic parametric approximations. Why not give them a try?” But today, the theory, the software, and the hardware have come together. Distribution-free permutation procedures are the primary method for testing hypotheses. Parametric procedures and the bootstrap are to be reserved for the few situations in which they may be applicable. Four factors have forced this change: 1. Desire by workers in applied ?elds to use the most powerful statistic for their applications. Such workers may not be aware of the fundamental lemma of Neyman and Pearson, but they know that the statistic they wanttouse—acomplexscoreoraratioofscores,doesnothaveanalready well-tabulated distribution. 2. Pressure from regulatory agencies for the use of methods that yield exact signi?cance levels, not approximations. 3. A growing recognition that most real-world data are drawn from mixtures of populations. 4. A growing recognition that missing data is inevitable, balanced designs the exception. Thus, it seems natural that the theory of testing hypothesis and the more general decision theory in which it is embedded should be introduced via the permutation tests. On the other hand, certain relatively robust param- ric tests such as Student’s t continue to play an essential role in statistical practice. Books > Statistics Soft cover, Springer Shop<
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This text is intended to provide a strong theoretical background in testing hypotheses and decision theory for those who will be practicing in the real worldorwhowillbeparticipatinginthet… Mehr…
This text is intended to provide a strong theoretical background in testing hypotheses and decision theory for those who will be practicing in the real worldorwhowillbeparticipatinginthetrainingofreal-worldstatisticiansand biostatisticians. In previous editions of this text, my rhetoric was somewhat tentative. I was saying, in e?ect, "Gee guys, permutation methods provide a practical real-world alternative to asymptotic parametric approximations. Why not give them a try?" But today, the theory, the software, and the hardware have come together. Distribution-free permutation procedures are the primary method for testing hypotheses. Parametric procedures and the bootstrap are to be reserved for the few situations in which they may be applicable. Four factors have forced this change: 1. Desire by workers in applied ?elds to use the most powerful statistic for their applications. Such workers may not be aware of the fundamental lemma of Neyman and Pearson, but they know that the statistic they wanttouse-acomplexscoreoraratioofscores,doesnothaveanalready well-tabulated distribution. 2. Pressure from regulatory agencies for the use of methods that yield exact signi?cance levels, not approximations. 3. A growing recognition that most real-world data are drawn from mixtures of populations. 4. A growing recognition that missing data is inevitable, balanced designs the exception. Thus, it seems natural that the theory of testing hypothesis and the more general decision theory in which it is embedded should be introduced via the permutation tests. On the other hand, certain relatively robust param- ric tests such as Student''s t continue to play an essential role in statistical practice. Books > Business > Markets List_Books, [PU: Springer]<
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(*) Derzeit vergriffen bedeutet, dass dieser Titel momentan auf keiner der angeschlossenen Plattform verfügbar ist.
This text is intended to provide a strong theoretical background in testing hypotheses and decision theory for those who will be practicing in the real worldorwhowillbeparticipatinginthet… Mehr…
This text is intended to provide a strong theoretical background in testing hypotheses and decision theory for those who will be practicing in the real worldorwhowillbeparticipatinginthetrainingofreal-worldstatisticiansand biostatisticians. In previous editions of this text, my rhetoric was somewhat tentative. I was saying, in e?ect, "Gee guys, permutation methods provide a practical real-world alternative to asymptotic parametric approximations. Why not give them a try?" But today, the theory, the software, and the hardware have come together. Distribution-free permutation procedures are the primary method for testing hypotheses. Parametric procedures and the bootstrap are to be reserved for the few situations in which they may be applicable. Four factors have forced this change: 1. Desire by workers in applied ?elds to use the most powerful statistic for their applications. Such workers may not be aware of the fundamental lemma of Neyman and Pearson, but they know that the statistic they wanttouse-acomplexscoreoraratioofscores,doesnothaveanalready well-tabulated distribution. 2. Pressure from regulatory agencies for the use of methods that yield exact signi?cance levels, not approximations. 3. A growing recognition that most real-world data are drawn from mixtures of populations. 4. A growing recognition that missing data is inevitable, balanced designs the exception. Thus, it seems natural that the theory of testing hypothesis and the more general decision theory in which it is embedded should be introduced via the permutation tests. On the other hand, certain relatively robust param- ric tests such as Student''s t continue to play an essential role in statistical practice. Books List_Books, [PU: Springer]<
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[EAN: 9781441919076], Nouveau livre, [SC: 19.9], [PU: Springer New York], CALCULUS; EFFICIENCY; CLUSTERING; PERMUTATIONTESTS, Druck auf Anfrage Neuware - Previous edition sold over 1400 c… Mehr…
[EAN: 9781441919076], Nouveau livre, [SC: 19.9], [PU: Springer New York], CALCULUS; EFFICIENCY; CLUSTERING; PERMUTATIONTESTS, Druck auf Anfrage Neuware - Previous edition sold over 1400 copies worldwide.This new edition includes many more real-world illustrations from biology, business, clinical trials, economics, geology, law, medicine, social science and engineering along with twice the number of exercises. 340 pp. Englisch, Books<
Paperback, [PU: Springer-Verlag New York Inc.], Previous edition sold over 1400 copies worldwide.
This new edition includes many more real-world illustrations from biology, business,… Mehr…
Paperback, [PU: Springer-Verlag New York Inc.], Previous edition sold over 1400 copies worldwide.
This new edition includes many more real-world illustrations from biology, business, clinical trials, economics, geology, law, medicine, social science and engineering along with twice the number of exercises., Probability & Statistics<
This text is intended to provide a strong theoretical background in testing hypotheses and decision theory for those who will be practicing in the real worldorwhowillbeparticipatinginthet… Mehr…
This text is intended to provide a strong theoretical background in testing hypotheses and decision theory for those who will be practicing in the real worldorwhowillbeparticipatinginthetrainingofreal-worldstatisticiansand biostatisticians. In previous editions of this text, my rhetoric was somewhat tentative. I was saying, in e?ect, “Gee guys, permutation methods provide a practical real-world alternative to asymptotic parametric approximations. Why not give them a try?” But today, the theory, the software, and the hardware have come together. Distribution-free permutation procedures are the primary method for testing hypotheses. Parametric procedures and the bootstrap are to be reserved for the few situations in which they may be applicable. Four factors have forced this change: 1. Desire by workers in applied ?elds to use the most powerful statistic for their applications. Such workers may not be aware of the fundamental lemma of Neyman and Pearson, but they know that the statistic they wanttouse—acomplexscoreoraratioofscores,doesnothaveanalready well-tabulated distribution. 2. Pressure from regulatory agencies for the use of methods that yield exact signi?cance levels, not approximations. 3. A growing recognition that most real-world data are drawn from mixtures of populations. 4. A growing recognition that missing data is inevitable, balanced designs the exception. Thus, it seems natural that the theory of testing hypothesis and the more general decision theory in which it is embedded should be introduced via the permutation tests. On the other hand, certain relatively robust param- ric tests such as Student’s t continue to play an essential role in statistical practice. Books > Statistics Soft cover, Springer Shop<
new in stock. Versandkosten:zzgl. Versandkosten. (EUR 0.00)
This text is intended to provide a strong theoretical background in testing hypotheses and decision theory for those who will be practicing in the real worldorwhowillbeparticipatinginthet… Mehr…
This text is intended to provide a strong theoretical background in testing hypotheses and decision theory for those who will be practicing in the real worldorwhowillbeparticipatinginthetrainingofreal-worldstatisticiansand biostatisticians. In previous editions of this text, my rhetoric was somewhat tentative. I was saying, in e?ect, "Gee guys, permutation methods provide a practical real-world alternative to asymptotic parametric approximations. Why not give them a try?" But today, the theory, the software, and the hardware have come together. Distribution-free permutation procedures are the primary method for testing hypotheses. Parametric procedures and the bootstrap are to be reserved for the few situations in which they may be applicable. Four factors have forced this change: 1. Desire by workers in applied ?elds to use the most powerful statistic for their applications. Such workers may not be aware of the fundamental lemma of Neyman and Pearson, but they know that the statistic they wanttouse-acomplexscoreoraratioofscores,doesnothaveanalready well-tabulated distribution. 2. Pressure from regulatory agencies for the use of methods that yield exact signi?cance levels, not approximations. 3. A growing recognition that most real-world data are drawn from mixtures of populations. 4. A growing recognition that missing data is inevitable, balanced designs the exception. Thus, it seems natural that the theory of testing hypothesis and the more general decision theory in which it is embedded should be introduced via the permutation tests. On the other hand, certain relatively robust param- ric tests such as Student''s t continue to play an essential role in statistical practice. Books > Business > Markets List_Books, [PU: Springer]<
This text is intended to provide a strong theoretical background in testing hypotheses and decision theory for those who will be practicing in the real worldorwhowillbeparticipatinginthet… Mehr…
This text is intended to provide a strong theoretical background in testing hypotheses and decision theory for those who will be practicing in the real worldorwhowillbeparticipatinginthetrainingofreal-worldstatisticiansand biostatisticians. In previous editions of this text, my rhetoric was somewhat tentative. I was saying, in e?ect, "Gee guys, permutation methods provide a practical real-world alternative to asymptotic parametric approximations. Why not give them a try?" But today, the theory, the software, and the hardware have come together. Distribution-free permutation procedures are the primary method for testing hypotheses. Parametric procedures and the bootstrap are to be reserved for the few situations in which they may be applicable. Four factors have forced this change: 1. Desire by workers in applied ?elds to use the most powerful statistic for their applications. Such workers may not be aware of the fundamental lemma of Neyman and Pearson, but they know that the statistic they wanttouse-acomplexscoreoraratioofscores,doesnothaveanalready well-tabulated distribution. 2. Pressure from regulatory agencies for the use of methods that yield exact signi?cance levels, not approximations. 3. A growing recognition that most real-world data are drawn from mixtures of populations. 4. A growing recognition that missing data is inevitable, balanced designs the exception. Thus, it seems natural that the theory of testing hypothesis and the more general decision theory in which it is embedded should be introduced via the permutation tests. On the other hand, certain relatively robust param- ric tests such as Student''s t continue to play an essential role in statistical practice. Books List_Books, [PU: Springer]<
[EAN: 9781441919076], Nouveau livre, [SC: 19.9], [PU: Springer New York], CALCULUS; EFFICIENCY; CLUSTERING; PERMUTATIONTESTS, Druck auf Anfrage Neuware - Previous edition sold over 1400 c… Mehr…
[EAN: 9781441919076], Nouveau livre, [SC: 19.9], [PU: Springer New York], CALCULUS; EFFICIENCY; CLUSTERING; PERMUTATIONTESTS, Druck auf Anfrage Neuware - Previous edition sold over 1400 copies worldwide.This new edition includes many more real-world illustrations from biology, business, clinical trials, economics, geology, law, medicine, social science and engineering along with twice the number of exercises. 340 pp. Englisch, Books<
Paperback, [PU: Springer-Verlag New York Inc.], Previous edition sold over 1400 copies worldwide.
This new edition includes many more real-world illustrations from biology, business,… Mehr…
Paperback, [PU: Springer-Verlag New York Inc.], Previous edition sold over 1400 copies worldwide.
This new edition includes many more real-world illustrations from biology, business, clinical trials, economics, geology, law, medicine, social science and engineering along with twice the number of exercises., Probability & Statistics<
1Da einige Plattformen keine Versandkonditionen übermitteln und diese vom Lieferland, dem Einkaufspreis, dem Gewicht und der Größe des Artikels, einer möglichen Mitgliedschaft der Plattform, einer direkten Lieferung durch die Plattform oder über einen Drittanbieter (Marketplace), etc. abhängig sein können, ist es möglich, dass die von eurobuch angegebenen Versandkosten nicht mit denen der anbietenden Plattform übereinstimmen.
Previous edition sold over 1400 copies worldwide.This new edition includes many more real-world illustrations from biology, business, clinical trials, economics, geology, law, medicine, social science and engineering along with twice the number of exercises.
Detailangaben zum Buch - Permutation, Parametric, and Bootstrap Tests of Hypotheses
EAN (ISBN-13): 9781441919076 ISBN (ISBN-10): 1441919074 Gebundene Ausgabe Taschenbuch Erscheinungsjahr: 2010 Herausgeber: Springer 340 Seiten Gewicht: 0,586 kg Sprache: eng/Englisch
Buch in der Datenbank seit 2011-03-11T22:54:57+01:00 (Berlin) Detailseite zuletzt geändert am 2022-04-09T15:35:27+02:00 (Berlin) ISBN/EAN: 9781441919076
ISBN - alternative Schreibweisen: 1-4419-1907-4, 978-1-4419-1907-6 Alternative Schreibweisen und verwandte Suchbegriffe: Autor des Buches: good Titel des Buches: permutation tests, permutation parametric bootstrap, bootstrap example
Daten vom Verlag:
Autor/in: Phillip I. Good Titel: Springer Series in Statistics; Permutation, Parametric, and Bootstrap Tests of Hypotheses Verlag: Springer; Springer US 316 Seiten Erscheinungsjahr: 2010-12-01 New York; NY; US Gedruckt / Hergestellt in Niederlande. Gewicht: 0,592 kg Sprache: Englisch 128,39 € (DE) 131,99 € (AT) 142,00 CHF (CH) POD XX, 316 p. 14 illus.
BC; Statistical Theory and Methods; Hardcover, Softcover / Mathematik/Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik; Wahrscheinlichkeitsrechnung und Statistik; Verstehen; calculus; clustering; efficiency; permutation tests; Statistics for Life Sciences, Medicine, Health Sciences; Statistics for Business, Management, Economics, Finance, Insurance; Statistical Theory and Methods; Biostatistics; Statistics in Business, Management, Economics, Finance, Insurance; Wirtschaftswissenschaft, Finanzen, Betriebswirtschaft und Management; BB
A Wide Range of Applications.- Optimal Procedures.- Testing Hypotheses.- Distributions.- Multiple Tests.- Experimental Designs.- Multifactor Designs.- Categorical Data.- Multivariate Analysis.- Clustering in Time and Space.- Coping with Disaster.- Solving the Unsolved and the Insolvable.- Publishing Your Results.- Increasing Computational Efficiency.
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