Study Design: The Basics -- Observational Study Design -- Descriptive Statistics -- Basic Principles of Statistical Inference -- Statistical Inference on Categorical Variables -- Development and Evaluation of Classifiers -- Comparison of Means -- Correlation and Simple Linear Regression -- Multiple Linear Regression -- General Linear Models -- Linear Mixed Effects Models -- Design and Analysis of Experiments -- Analysis of Change -- Logistic Regression -- Survival Analysis -- Basic Bayesian Methods -- Overview of Missing Data Techniques -- Statistical Topics in the Laboratory Sciences -- Power and Sample Size -- Microarray Analysis -- Association Methods in Human Genetics -- Genome Mapping Statistics and Bioinformatics -- Working with a Statistician.

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.