ISBN: 978-0-470-23146-3
Hardcover
512 pages
July 2009
A result of the author's 30 years of practical teaching experience, this Second Edition provides a modern approach to a number of statistical model concepts that are linear in the unknown parameters and include a random error term. Now featuring a thorough discussion of mixed models, nonparametric regression, and Bayesian models, this textbook for graduate students follows an introduction-theorem-proof-examples format that allows for easier comprehension of how to use the methods and also how to recognize the associated assumptions and limits.
ISBN: 978-0-471-69946-0
Hardcover
744 pages
July 2009
Experimentation is one of the most common activities in which all people engage. In this thoroughly updated Second Edition, Experiments presents the most modern, up-to-date treatment in the design and analysis of experiment topics currently available. The authors?highly recognized researchers in the field?introduce some of the newest discoveries and shed further light on existing ones. Drawing from their impressive roster of industrial clients, the authors modernize accepted methodologies while refining many cutting-edge topics in a single, easily accessible source suitable for upper-undergraduate or beginning-graduate students, practicing engineers, and statisticians.
ISBN: 978-0-470-41169-8
Hardcover
512 pages
October 2009
Written by well-known, award-winning authors, this is the first book to focus on high-dimensional data analysis while presenting real-world applications and research material. Emphasizing that high-dimensional asymptotic distribution can be used for a large range of samples and dimensions to achieve high levels of accuracy, this timely text provides approximation formulas, actual applications, thorough analysis of the real data, and solutions to each problem that are useful to both practical and theoretical statisticians as well as graduate students.
ISBN: 978-0-470-49949-8
Hardcover
592 pages
November 2009
This new book for mathematics teachers helps them gain an appreciation of geometry and its importance in the history and development of mathematics. The material is presented in three parts. The first is devoted to Euclidean geometry. The second covers non-Euclidean geometry. The last part explores symmetry. Exercises and activities are interwoven with the text to enable them to explore geometry. The activities take advantage of geometric software so theyfll gain a better understanding of its capabilities. Mathematics teachers will be able to use this material to create exciting and engaging projects in the classroom.
ISBN: 978-0-470-74304-1
Hardcover
376 pages
December 2009
A self-contained introduction to the theory and applications of Bayesian Networks
Bayesian networks are a topic of interest and importance for statisticians, computer scientists and those involved in modelling and the learning of complex data sets. The material included in this introductory guide has been extensively tested in classroom teaching and assumes a basic knowledge of probability and statistics course and basic mathematics. All notions are explained carefully with an extensive set of exercises throughout the book as well as computer exercises. A solutions manual is also provided online.