This book aims to compile typical fundamental-to-advanced statistical methods to be used for health
data sciences. Although the book promotes applications to health and health-related data, the
models in the book can be used to analyze any kind of data. The data are analyzed with the commonly
used statistical software of R/SAS (with online supplementary on SPSS/Stata). The data and
computing programs will be available to facilitate readers' learning experience. There has been
considerable attention to making statistical methods and analytics available to health data science
researchers and students. This book brings it all together to provide a concise point-of-reference
for the most commonly used statistical methods from the fundamental level to the advanced level. We
envisage this book will contribute to the rapid development in health data science. We provide
straightforward explanations of the collected statistical theory and models, compilations of a
variety of publicly available data, and illustrations of data analytics using commonly used
statistical software of SAS/R. We will have the data and computer programs available for readers to
replicate and implement the new methods. The primary readers would be applied data scientists and
practitioners in any field of data science, applied statistical analysts and scientists in public
health, academic researchers, and graduate students in statistics and biostatistics. The secondary
readers would be R&D professionals/practitioners in industry and governmental agencies. This
book can be used for both teaching and applied research.