This book presents a multidisciplinary survey of biostatics methods, each illustrated with hands-on examples. It introduces advanced methods in statistics, including how to choose and work with statistical packages. Specific topics of interest include microarray analysis, missing data techniques, power and sample size, statistical methods in genetics. The book is an essential resource for researchers at every level of their career.
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From the reviews:
"It is useful to biologists as well as statisticians. The book describes the use of appropriate statistical methods and offers guidelines on selecting an appropriate test. ... The main strength of the book is the clear exposition of statistical tests. ... As biostatisticians we strongly recommend this book for libraries where research on molecular biology is going on, and students ... in biostatistics. ... helpful in understanding the essence of the statistical techniques to a wide range of researchers and students in biology and medicine." (Mukesh Srivastava and M. Abbas, Journal of Applied Statistics, Vol. 36 (4), April, 2009)
Biostatistics can be a language nearly indecipherable to those not trained to speak it. In Topics in Biostatistics, a broad survey of biostatiscal methods, techniques are illustrated by clear, step-by-step instructions able to be performed with paper, a pencil, and a calculator. With subjects as diverse as descriptive statistics, study design, statistical inference, and linear and logistic regression, this volume invites the reader to better understand the language of statistics to aid in collaborations with biostatisticians or the deciphering of software manuals. Following the format of the highly successful Methods in Molecular Biology™ format, each protocol offers readily reproducible results, and, specifically in this case, provides the reader with a concise introduction to complicated statistical methods.
Comprehensive and enlightening, Topics in Biostatistics is the perfect statistical resource for scientists in all disciplines attempting to comprehend this challenging mathematical field.
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