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ISBN 10: 3030990907 ISBN 13: 9783030990909
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a coherent description of foundational matters concerning statistical inference and shows how statistics can help us make inductive inferences about a broader context, based only on a limited dataset such as a random sample drawn from a larger population. By relating those basics to the methodological debate about inferential errors associated withp-values and statistical significance testing, readers are provided with a clear grasp of what statistical inference presupposes, and what it can and cannot do. To facilitate intuition, the representations throughout the book are as non-technical as possible.The central inspiration behind the text comes from the scientific debate about good statistical practices and the replication crisis. Calls for statistical reform include an unprecedented methodological warning from theAmerican Statistical Associationin 2016, a special issue 'Statistical Inference in the 21st Century:A World BeyondpThe American Statisticianin 2019, and a widely supported call to 'Retire statistical significance' inNaturein 2019.The book elucidates the probabilistic foundations and the potential of sample-based inferences, including random data generation, effect size estimation, and the assessment of estimation uncertainty caused by random error. Based on a thorough understanding of those basics, it then describes thep-value concept and the null-hypothesis-significance-testing ritual, and finally points out the ensuing inferential errors. This provides readers with the competence to avoid ill-guided statistical routines and misinterpretations of statistical quantities in the future.Intended for readers with an interest in understanding the role of statistical inference, the book provides a prudent assessment of the knowledge gain that can be obtained from a particular setof data under consideration of the uncertainty caused by random error. More particularly, it offers an accessible resource for graduate students as well as statistical practitioners who have a basic knowledge of statistics. Last but not least, it is aimed at scientists with a genuine methodological interest in the above-mentioned reform debate.
Idioma: Inglés
Publicado por Springer Nature Switzerland AG, CH, 2022
ISBN 10: 3030990907 ISBN 13: 9783030990909
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Añadir al carritoTaschenbuch. Condición: Neu. Fundamentals of Statistical Inference | What is the Meaning of Random Error? | Norbert Hirschauer (u. a.) | Taschenbuch | SpringerBriefs in Applied Statistics and Econometrics | xv | Englisch | 2022 | Springer | EAN 9783030990909 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Añadir al carritoCondición: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | - 1. Introduction. - 2. The Meaning of Scientific and Statistical Inference. - 3. The Basics of Statistical Inference: Simple Random Sampling. - 4. Estimation Uncertainty in Complex Sampling Designs. - 5. Knowledge Accumulation Through Meta-analysis and Replications. - 6. The p-Value and Statistical Significance Testing. - 7. Statistical Inference in Experiments. - 8. Better Inference in the 21st Century: A World Beyond p < 0.05.
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Idioma: Inglés
Publicado por Springer International Publishing, Springer Nature Switzerland Aug 2022, 2022
ISBN 10: 3030990907 ISBN 13: 9783030990909
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides a coherent description of foundational matters concerning statistical inference and shows how statistics can help us make inductive inferences about a broader context, based only on a limited dataset such as a random sample drawn from a larger population. By relating those basics to the methodological debate about inferential errors associated withp-values and statistical significance testing, readers are provided with a clear grasp of what statistical inference presupposes, and what it can and cannot do. To facilitate intuition, the representations throughout the book are as non-technical as possible.The central inspiration behind the text comes from the scientific debate about good statistical practices and the replication crisis. Calls for statistical reform include an unprecedented methodological warning from theAmerican Statistical Associationin 2016, a special issue 'Statistical Inference in the 21st Century:A World BeyondpThe American Statisticianin 2019, and a widely supported call to 'Retire statistical significance' inNaturein 2019.The book elucidates the probabilistic foundations and the potential of sample-based inferences, including random data generation, effect size estimation, and the assessment of estimation uncertainty caused by random error. Based on a thorough understanding of those basics, it then describes thep-value concept and the null-hypothesis-significance-testing ritual, and finally points out the ensuing inferential errors. This provides readers with the competence to avoid ill-guided statistical routines and misinterpretations of statistical quantities in the future.Intended for readers with an interest in understanding the role of statistical inference, the book provides a prudent assessment of the knowledge gain that can be obtained from a particular setof data under consideration of the uncertainty caused by random error. More particularly, it offers an accessible resource for graduate students as well as statistical practitioners who have a basic knowledge of statistics. Last but not least, it is aimed at scientists with a genuine methodological interest in the above-mentioned reform debate. 148 pp. Englisch.
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Idioma: Inglés
Publicado por Springer International Publishing, 2022
ISBN 10: 3030990907 ISBN 13: 9783030990909
Librería: moluna, Greven, Alemania
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Añadir al carritoKartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Facilitates effective intuition of what statistical inference presupposes, and what it can and cannot doElaborates on the ongoing debate about inferential errors related to p-values and statistical significance testingProvides a non-technic.
Idioma: Inglés
Publicado por Springer, Springer Aug 2022, 2022
ISBN 10: 3030990907 ISBN 13: 9783030990909
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book provides a coherent description of foundational matters concerning statistical inference and shows how statistics can help us make inductive inferences about a broader context, based only on a limited dataset such as a random sample drawn from a larger population. By relating those basics to the methodological debate about inferential errors associated with p-values and statistical significance testing, readers are provided with a clear grasp of what statistical inference presupposes, and what it can and cannot do. To facilitate intuition, the representations throughout the book are as non-technical as possible.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 148 pp. Englisch.