The Handbook of Statistical Analysis and Data Mining Applications is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers (both academic and industrial) through all stages of data analysis, model building and implementation. The Handbook helps one discern the technical and business problem, understand the strengths and weaknesses of modern data mining algorithms, and employ the right statistical methods for practical application.
Use this book to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques, and discusses their application to real problems, in ways accessible and beneficial to practitioners across industries – from science and engineering, to medicine, academia and commerce. This handbook brings together, in a single resource, all the information a beginner will need to understand the tools and issues in data mining to build successful data mining solutions.
Authors: Robert Nisbet, Ph.D. John Elder, IV, Ph.D. Gary Miner, Ph.D. Published June 5, 2009, Elsevier Publishing
- Awarded the 2009 American Publishers PROSE (Professional and Scholarly Excellence) award for mathematics. The PROSE awards annually recognize the very best in professional and scholarly publishing.
- Written “by practitioners for practitioners”
- Non-technical explanations build understanding without jargon and equations
- Tutorials in numerous fields of study provide step-by-step instruction on how to use supplied tools to build models using Statistica, SAS and SPSS software
- Practical advice from successful real-world implementations
- Includes extensive case studies, examples, MS PowerPoint slides and datasets
- CD-DVD with valuable fully-working 90-day software included: “Complete Data Miner – QC-Miner – Text Miner” bound with book