Introductory Biostatistics

Praise for the First Edition

Students from health, medical, pharmacy, and nursing will find...Introductory Biostatistics extremely useful. Difficult biostatistical concepts are made easier by simple and careful explanations..."

– Journal of Statistical Computation and Simulation

Maintaining the same accessible and hands–on presentation, Introductory Biostatistics, Second Edition continues to provide an organized introduction to basic statistical concepts commonly applied in research across the health sciences. With plenty of real–world examples, the new edition provides a practical, modern approach to the statistical topics found in the biomedical and public health fields.

Beginning with an overview of descriptive statistics in the health sciences, the book delivers topical coverage of probability models, parameter estimation, and hypothesis testing. Subsequently, the book focuses on more advanced topics with coverage of regression analysis, logistic regression, methods for count data, analysis of survival data, and designs for clinical trials. Featuring a thorough update, Introductory Biostatistics, Second Edition includes:

A new chapter on the use of higher order Analysis of Variance (ANOVA) in factorial and block designs A new chapter on testing and inference methods for repeatedly measured outcomes including continuous, binary, and count outcomes R incorporated throughout along with SAS®, allowing readers to replicate results from presented examples with either software Multiple additional exercises, with partial solutions available to aid comprehension of crucial concepts Notes on Computations sections to provide further guidance on the use of software A related website that hosts the large data sets presented throughout the book

Introductory Biostatistics, Second Edition is an excellent textbook for upper–undergraduate and graduate students in introductory biostatistics courses. The book is also an ideal reference for applied statisticians working in the fields of public health, nursing, dentistry, and medicine.

Chap T. Le, PhD, is Distinguished Professor of Biostatistics and Director of Biostatistics and Bioinformatics at the University of Minnesota Masonic Cancer Center. He has provided statistical consulting for a variety of biomedical research projects, and he has worked on collaborations that have focused on the analyses of survival and categorical data and, currently, in the areas of cancer and tobacco research. Dr. Le is the author of Health and Numbers: A Problems–Based Introduction to Biostatistics, Third Edition; Applied Categorical Data Analysis and Translational Research, Second Edition and Applied Survival Analysis, all published by Wiley.

Lynn E. Eberly, PhD, is Associate Professor in the Division of Biostatistics at the University of Minnesota. The author of more than 100 journal articles, Dr. Eberly has been a statistical collaborator in biomedical and public health research for more than 15 years. Her current research interests include methods for and applications to correlated data in neurodegenerative conditions, endocrinology, psychiatry/psychology, and cancer research.