The growing interest in data mining is motivated by a common problem across disciplines: how does one store, access, model, and ultimately describe and understand very large data sets? Historically, different aspects of data mining have been addressed independently by different disciplines. This is the first truly...

This timely book, A Matrix Handbook for Statisticians, provides a comprehensive, encyclopedic treatment of matrices as they relate to both statistical concepts and methodologies. Written by an experienced authority on matrices and...

Excel has become an important and nearly ubiquitous classroom and office resource for students and practitioners who are faced with solving statistical problems on an everyday basis. Despite this, there has yet to emerge a truly practical, “how-do-I-do-it” manual that teaches the various applications and...

A complete introduction and guide to the latest developments in cancer gene therapy-from bench to bedside. The authors comprehensively review the anticancer genes and gene delivery methods currently available for cancer gene therapy, including the transfer of genetic material into the cancer cells, stimulation of the immune system to...

"The first edition of the book was one of the first books in the excellent Wiley U.K. series on...

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most...

The book begins with an introduction to analytics, analytical tools, and SAS programming. The authors—both SAS, statistics, analytics, and big data...

Stymied by SPSS? This friendly, plain-English guide gets you up and running with the latest version of the software so that you can start performing calculations...