Biostatistics with R - (Use R!) by Babak Shahbaba (Paperback)

About the Book

Biostatistics with R is designed to mimic the interaction between theory and application in statistics. Topics include data exploration, estimation, and clustering with two appendices on installing and running R and R-commander.

Book Synopsis

Biostatistics with R is designed around the dynamic interplay among statistical methods, their applications in biology, and their implementation. The book explains basic statistical concepts with a simple yet rigorous language. The development of ideas is in the context of real applied problems, for which step-by-step instructions for using R and R-Commander are provided. Topics include data exploration, estimation, hypothesis testing, linear regression analysis, and clustering with two appendices on installing and using R and R-Commander. A novel feature of this book is an introduction to Bayesian analysis.

This author discusses basic statistical analysis through a series of biological examples using R and R-Commander as computational tools. The book is ideal for instructors of basic statistics for biologists and other health scientists. The step-by-step application of statistical methods discussed in this book allows readers, who are interested in statistics and its application in biology, to use the book as a self-learning text.

From the Back Cover

Biostatistics with R is designed around the dynamic interplay among statistical methods, their applications in biology, and their implementation. The book explains basic statistical concepts with a simple yet rigorous language. The development of ideas is in the context of real applied problems, for which step-by-step instructions for using R and R-Commander are provided. Topics include data exploration, estimation, hypothesis testing, linear regression analysis, and clustering with two appendices on installing and using R and R-Commander. A novel feature of this book is an elementary introduction to the basic of Bayesian analysis.

This author discusses basic statistical analysis through a series of biological examples using R and R-Commander as computational tools. The book is ideal for instructors of basic statistics for biologists and other health scientists. The step-by-step application of statistical methods discussed in this book allows readers, who are interested in statistics and its application in biology, to use the book as a self-learning text.

Review Quotes

From the reviews:

"It presents the statistical concepts/methods starting with biological examples and leads the reader using R commands as guidelines. The author uses all opportunities to emphasize the close connection between statistics and other fields, making this textbook a good start for interdisciplinary studies. ... written for a broad range of readers, from undergraduates to researchers, from readers with a strong statistical background who wish to understand how to approach biological data sets, to readers who wish to use statistical methods to mine for information." (Irina Ioana Mohorianu, zbMATH, Vol. 1275, 2014)

This book is, however, unique and distinct from others in the field that it presents R-Commander - a useful tool for teaching basic statistics to students who do not have a computer programming background. The Appendix A provides the simple instructions for its installation on a computer and introduces the reader to the R-Commander window. The author presents statistical methods by their direct application to numerous past scientific studies that are publicly available. In addition, the various data sets are available online and can be downloaded which makes the text ideal as a teaching aid. A balance has been struck between mathematical rigour and readability; with more complex concepts that are of limited application in everyday analyses relegated to the end of each chapter in Advanced sections.
International Statistical Review, 81, 3, 2013, Review by Carl M.O'Brien

About the Author

Babak Shahbaba is Assistant Professor of Biostatistics at the University of California, Irvine, where he has been teaching undergraduate courses such as Introduction to Biostatistics, and graduate courses such as Advanced Statistical Methods and Bayesian Analysis. His research interest is related to developing novel statistical methods to answer research questions in genomics, proteomics, and cancer studies.