Handbook of Statistical Analysis and Data Mining Applications

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.

• 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

• IBM SPSS Modeler Cookbook
• Applied Predictive Modeling
• Applied Predictive Analytics
• Ensemble Methods in Data Mining: Improving Accuracy Through Combining Predictions (Synthesis Lectures on Data Mining and Knowledge Discovery)
• Machine Learning with R: Expert techniques for predictive modeling, 3rd Edition
• Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking
• Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems
• IBM SPSS Modeler Essentials: Effective techniques for building powerful data mining and predictive analytics solutions
• Handbook of Statistical Analysis and Data Mining Applications
• Data Mining and Statistics for Decision Making