Biostatistics: A Foundation for Analysis in the Health Sciences (Wiley Series in Probability and Statistics). This item is unavailable.Biostatistics: A Foundation for Analysis in the Health Sciences (Wiley Series in Probability and Statistics)

This successful text offers comprehensive coverage of statistics with applications to the medical and public health fields. The book will appeal to advanced undergraduates or graduate students in need of a reference book on methodology but requires a reasonable proficiency in algebra. The focus of Biostatistics is an intuitive understanding of principles rather than mathematical sophistication. The previous edition of this book was published in 1987.

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