Biostatistics: Basic Concepts and Methodology for the Health Sciences (Wiley Series in Probability and Statistics)

Daniel, Wayne W.

ISBN 10: 0470413336 / ISBN 13: 9780470413333

Edité par John Wiley & Sons, 2009

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Most items will be dispatched the same or the next working day. A copy that has been read but remains in clean condition. All of the pages are intact and the cover is intact and the spine may show signs of wear. The book may have minor markings which are not specifically mentioned. N° de réf. du vendeur wbb0020950205

Détails bibliographiques

Titre : Biostatistics: Basic Concepts and ...

Éditeur : John Wiley & Sons

Date d'édition : 2009

Reliure : Couverture souple

Etat : Good

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Develop the statistical tools needed in the allied health fields  

Anyone entering the allied health field needs to have a working understanding of how data can be turned into useful information. Now in its ninth edition, Wayne W. Daniel s Biostatistics: A Foundation for Analysis in the Health Sciences provides a comprehensive introduction to biostatistics as it is used in the biological sciences.

Designed for the undergraduate and graduate student across a range of fields, from the health disciplines to forestry and animal husbandry, the text takes an applied and computer–oriented approach to its topical coverage. Its chapters take you from the basic concepts of probability through hypothesis testing, linear regression and correlation, the analysis of variance, chi–square distribution, nonparametric and distribution–free statistics, and more.

This new edition adds much new and expanded material, including such features as:

• Integration of new applications from several biological science fields throughout the pages
• Highlighting of main ideas with bulleted objectives at the start of each chapter
• Summary boxes of formulae and statistical rules for easy reference and review
• Support for multiple programs such as SPSS, SAS, and STATA, in addition to Minitab
• Screen captures and technology boxes with step–by–step help
• Real–world practice through examples and exercises using data from actual research projects and reports