What If There Were No Significance Tests?, Harlow, Lisa L.
Старое издание
Автор: Harlow, Lisa L. Название: What If There Were No Significance Tests? ISBN: 0805826343 ISBN-13(EAN): 9780805826340 Издательство: Taylor&Francis Цена: 19906.00 р. Наличие на складе: Поставка под заказ.
Автор: Harlow Название: What If There Were No Significance Tests? ISBN: 1138892475 ISBN-13(EAN): 9781138892477 Издательство: Taylor&Francis Рейтинг: Цена: 10104.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The classic edition of What If There Were No Significance Tests? highlights current statistical inference practices. Four areas are featured as essential for making inferences: sound judgment, meaningful research questions, relevant design, and assessing fit in multiple ways.
Описание: Provides the tools needed to successfully perform adaptive tests across a broad range of datasets Adaptive Tests of Significance Using Permutations of Residuals with R and SAS illustrates the power of adaptive tests and showcases their ability to adjust the testing method to suit a particular set of data.
Автор: Henkel, Ramon E. Название: The Significance Test Controversy ISBN: 0202308790 ISBN-13(EAN): 9780202308791 Издательство: Taylor&Francis Рейтинг: Цена: 7348.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Lecoutre, Bruno Poitevineau, Jacques Название: Significance test controversy revisited ISBN: 366265704X ISBN-13(EAN): 9783662657041 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book explains the misuses and abuses of Null Hypothesis Significance Tests, which are reconsidered in light of Jeffreys’ Bayesian concept of the role of statistical inference, in experimental investigations. Minimizing the technical aspects, the studies focuses mainly on methodological contributions. The first part of the book gives an overview of the major approaches to statistical testing and an enlightening discussion of the philosophies of Fisher, Neyman-Pearson and Jeffrey. The conceptual and methodological implications of current practices of reporting effect sizes and confidence intervals are also examined and challenged. This sheds new light on the "significance testing controversy" and provides an appropriate Bayesian framework for a comprehensive approach to the analysis and interpretation of experimental data. The second part of the book provides concrete Bayesian routine procedures that bypass common misuses of significance testing and are readily applicable in a wide range of real applications. This approach addresses the need for objective reporting of experimental data, that is acceptable to the scientific community. This is emphasized by the name fiducial (from the Latin fiducia = confidence). The fiducial Bayesian procedures provide the reader with a real opportunity to think sensibly about problems of statistical inference. This book prepares students and researchers to critically read statistical analyses reported in the literature and equips them with an appropriate alternative to the use of significance testing.
Автор: Ziliak, Stephen Thomas Mccloskey, Deirdre N. Название: Cult of statistical significance ISBN: 0472050079 ISBN-13(EAN): 9780472050079 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 3756.00 р. Наличие на складе: Нет в наличии.
Описание: Null hypothesis significance testing is a scientific train-wreck, about which a small group of statisticians have been warning. This book shows how the wreck happened, and reports on the fatalities. It shows how wide the disaster is, and traces the problem to its historical, sociological, and philosophical roots.
Автор: MacInnes John Название: Statistical Significance ISBN: 1526466783 ISBN-13(EAN): 9781526466785 Издательство: Sage Publications Рейтинг: Цена: 1582.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Do your results mean something - or not? How can you measure it? Breaking it down into three building blocks, this Little Quick Fix shows students how to master hypothesis testing, normal distribution and p values.
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