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Data Analysis with Small Samples and Non-Normal Data: Nonparametrics and Other Strategies, Siebert Carl F., Siebert Darcy Clay


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Автор: Siebert Carl F., Siebert Darcy Clay
Название:  Data Analysis with Small Samples and Non-Normal Data: Nonparametrics and Other Strategies
ISBN: 9780199391493
Издательство: Oxford Academ
Классификация:








ISBN-10: 0199391491
Обложка/Формат: Paperback
Страницы: 240
Вес: 0.28 кг.
Дата издания: 19.09.2017
Серия: Pocket guides to social work research methods
Язык: English
Размер: 141 x 209 x 15
Читательская аудитория: Professional & vocational
Подзаголовок: Nonparametrics and other strategies
Ссылка на Издательство: Link
Рейтинг:
Поставляется из: Англии
Описание: Written in everyday language for non-statisticians, this book provides all the information needed to successfully conduct nonparametric analyses. This ideal reference book provides step-by-step instructions to lead the reader through each analysis, screenshots of the software and output, and case scenarios to illustrate of all the analytic techniques.


Categorical and Nonparametric Data Analysis

Автор: Nussbaum E Michael
Название: Categorical and Nonparametric Data Analysis
ISBN: 1138787825 ISBN-13(EAN): 9781138787827
Издательство: Taylor&Francis
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Цена: 12248.00 р.
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Описание: Featuring in-depth coverage of categorical and nonparametric statistics, this book provides a conceptual framework for choosing the most appropriate type of test in various research scenarios. Class tested at the University of Nevada, the book's clear explanations of the underlying assumptions, computer simulations, and Exploring the Concept boxes help reduce reader anxiety. Problems inspired by actual studies provide meaningful illustrations of the techniques. The underlying assumptions of each test and the factors that impact validity and statistical power are reviewed so readers can explain their assumptions and how tests work in future publications. Numerous examples from psychology, education, and other social sciences demonstrate varied applications of the material. Basic statistics and probability are reviewed for those who need a refresher. Mathematical derivations are placed in optional appendices for those interested in this detailed coverage. Highlights include the following: Unique coverage of categorical and nonparametric statistics better prepares readers to select the best technique for their particular research project; however, some chapters can be omitted entirely if preferred. Step-by-step examples of each test help readers see how the material is applied in a variety of disciplines.  Although the book can be used with any program, examples of how to use the tests in SPSS and Excel foster conceptual understanding. Exploring the Concept boxes integrated throughout prompt students to review key material and draw links between the concepts to deepen understanding.  Problems in each chapter help readers test their understanding of the material.  Emphasis on selecting tests that maximize power helps readers avoid "marginally" significant results.  Website (www.routledge.com/9781138787827) features datasets for the book's examples and problems, and for the instructor, PowerPoint slides, sample syllabi, answers to the even-numbered problems, and Excel data sets for lecture purposes. Intended for individual or combined graduate or advanced undergraduate courses in categorical and nonparametric data analysis, cross-classified data analysis, advanced statistics and/or quantitative techniques taught in psychology, education, human development, sociology, political science, and other social and life sciences, the book also appeals to researchers in these disciplines. The nonparametric chapters can be deleted if preferred. Prerequisites include knowledge of t tests and ANOVA.


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