Permutation parametric bootstrap tests par good phillip (26 résultats)

Hardcover. Etat : Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

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Etat : Good. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Hardcover. Etat : Gut. Third Edition. 336 pp. Cover partially discolored. Name on endpaper, otherwise well preserved inside 378 Sprache: Englisch Gewicht in Gramm: 696.

Etat : New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

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Paperback. Etat : Good. Paperback. Third edition. Several scores on covers. Spine foot and lower edge of rear cover are a little bumped, affecting closing pages. Light wear on spine head and leading corners. Front upper leading corner is slightly bent, affecting early pages. Minor film peeling on leading edge of rear cover. Binding is intact, contents are clean and clear. AM. Used.…

hardcover. Etat : New. In shrink wrap. Looks like an interesting title.

Etat : New. In English.

Etat : New. In English.

Hardback. Etat : New. 3rd ed. 2005. 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.…

Etat : New.

Etat : As New. Unread book in perfect condition.

Taschenbuch. Etat : Neu. Permutation, Parametric, and Bootstrap Tests of Hypotheses | Phillip I. Good | Taschenbuch | xx | Englisch | 2010 | Springer | EAN 9781441919076 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.…

Etat : New. pp. 340 3rd Edition.

Hardback. Etat : New. 3rd ed. 2005. 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.…

Paperback. Etat : Brand New. 3rd ed. edition. 376 pages. 9.00x6.00x0.77 inches. In Stock.

Etat : new. Questo è un articolo print on demand.

Paperback / softback. Etat : New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Contains valuable techniques for reducing computation time, practical advice on experimental design, comparisons with bootstrap, parametric, and nonparametric techniques and a three-part bibliography featuring more than 1,000 articlesContains .…

Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Contains valuable techniques for reducing computation time, practical advice on experimental design, comparisons with bootstrap, parametric, and nonparametric techniques and a three-part bibliography featuring more than 1,000 articlesContains .…

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 340 pp. Englisch.…

Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 340 pp. Englisch.…

Etat : New. Print on Demand pp. 340 14 Illus.

Etat : New. PRINT ON DEMAND pp. 340.