Multivariate data analysis (MDA) is a standard course taught at graduate level in various departments, notably mathematics and statistics, but also epidemiology, social sciences, e...
This book provides a foundation for the application of methods for analyzing multivariate generalized linear mixed models using R. It covers the necessary background in GLMs, mixed...
This book shows the elements of statistical science that are highly relevant for students who plan to become data scientists. However, most of the content focuses on the statistica...
There are many methods for multiple testing adjustment and questions arise concerning when they should be used and how they may provide different results. This book focuses on mult...
This book provides a systematic account of robust statistical methods, an area where the existing literature is dated, narrow, or treated in an overly theoretical manner. The autho...
Bridging the gap between introductory theory and practical knowledge, this second edition reflects the fast-moving field of DNA microarrays by adding new and updated chapters that ...
Trial simulations provide a very useful tool in planning and designing successful clinical trials. Because so many different variables go into the design, conduct, and outcome of a...
The intended audience is leaders at financial institutions who want to build data science practices, analysts at financial institutions who want to work on data science teams, stud...
Text mining is a relatively new area that has seen a recent explosion in interest. It uses techniques from statistics, data mining and computer science and there is a need for a bo...
