Statistical research methods : a guide for non-statisticians

This textbook will help graduate students in non-statistics disciplines, advanced undergraduate researchers, and research faculty in the health sciences to learn, use and communicate results from many commonly used statistical methods. The material covered, and the manner in which it is presented, d...

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Главные авторы: Sabo, Roy, Boone, Edward (Автор)
Формат: Livre numérique
Язык:Anglais
Опубликовано: New York, NY : Springer New York 2013.
Cham : Springer Nature
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Edition sous un autre format:• Statistical Research Methods, Texte imprimé, 9781461487074
• Statistical Research Methods, Texte imprimé, 9781461487098
• Statistical Research Methods, Texte imprimé, 9781493945481
• Statistical Research Methods, Texte imprimé, 9781071601143
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245 1 0 |a Statistical research methods :  |b a guide for non-statisticians   |c by Roy Sabo, Edward Boone. 
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505 0 |a Introduction.- One-Sample Proportions.- Two-Sample Proportions.- Multi-Category Data -- Summarizing Continuous Data.- One-Sample Means -- Two-Sample Means.- Analysis of Variance.- Power and Sample-Size.- Association and Regression. 
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520 |a This textbook will help graduate students in non-statistics disciplines, advanced undergraduate researchers, and research faculty in the health sciences to learn, use and communicate results from many commonly used statistical methods. The material covered, and the manner in which it is presented, describe the entire data analysis process from hypothesis generation to writing the results in a manuscript. Chapters cover, among other topics: one and two-sample proportions, multi-category data, one and two-sample means, analysis of variance, and regression. Throughout the text, the authors explain statistical procedures and concepts using a non-statistical language. This accessible approach is complete with real-world examples and sample write-ups for the Methods and Results sections of scholarly papers. The text also allows for the concurrent use of the programming language R, which is an open-source program created, maintained and updated by the statistical community. R is freely available and easy to download. 
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