Introductory Biostatistics, Second Edition

Maintaining the same accessible and hands-on presentation as itspredecessor,Introductory Biostatistics, Second Editioncontinues to provide a problem-based approach to basic statisticalconcepts that are commonly applied in research across the healthsciences. The addition of a coauthor, incorporation of R softwarethroughout, and coverage of newly-added topics and examples allensure that this new edition provides a modern and firm foundationin biostatistics for readers and students in the biomedicaland public health fields. Throughout the book, real data setsare provided in the form of examples and exercises that illustratehow to apply the discussed statistical procedures. Most chaptersconclude with aNotes on Computations section that suppliesreaders with sample SAS and R codes along with insight on thefundamentals for working with these software programs. All chaptersconclude with a set of exercises with partial solutions at the endof the book, and a related website houses the presented data sets

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 focusing 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 18 years. Her current research interests include methods for and applications to correlated data in neurodegenerative conditions, endocrinology, psychiatry/psychology, and cancer research.