Knowledge of statistics is essential in modern biology and medicine. Biologists and health professionals learn statistics best with real and interesting examples. The Analysis of Biological Data, Second Edition, by Whitlock and Schluter, teaches modern methods of statistics through the use of fascinating biological and medical cases. Readers consistently praise its clear and engaging writing and practical perspective. The second edition features over 200 new examples and problems. These include new calculation practice problems, which guide the student step by step through the methods, and a greater number of the examples and topics come from medical and human health research. Every chapter has been carefully edited for even greater clarity and ease of use. All the data sets, R scripts for all worked examples in the book, as well as many other teaching resources, are available to qualified instructors (see below). The Analysis of Biological Data is the most widely adopted introductory biological statistics textbook. It is now used at well over 200 schools and on every continent.
This book is the first of its kind to bring together two important research areas, soft computing and bioinformatics, in order to demonstrate how the tools and techniques in the former can be used for efficiently solving several problems in ...
This volume also includes a section on advanced procedures and a chapter outlining algorithms and the art of programming using R. This second edition has been revised to be current with the versions of R software released since the book’s ...
A manual to teach people to use the statistical software package S-Plus and to support the process of learning statistical concepts and methods.
Many biologists remain unfamiliar with statistical analysis and modelling, yet need to apply these techniques increasingly in their research. This volume describes how to analyze biological data, with commonly available...
Kniha je zaměřena na regresní modely, konkrétně jednorozměrné zobecněné lineární modely (GLM).
The book includes feedback the editor received from students studying at both undergraduate and graduate levels, and from her peers.
This book is suitable as a resource for researchers in computer science, biology, bioinformatics, advanced biochemistry, and the life sciences, and also serves as an ideal reference text for graduate-level courses in bioinformatics and ...
Introduces biological concepts and biotechnologies producing the data, graph and network theory, cluster analysis and machine learning, using real-world biological and medical examples.
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 book also looks at sample preparation methods unique to various instruments and speciation chemistry issues, and examines the link between chemical analysis and specimen banking.