Data Analysis and Data Mining: An Introduction

Editorial Reviews

An introduction to statistical , Data and Data Mining: An Introduction is both textbook and professional resource. Assuming only a basic knowledge of statistical reasoning, it presents core concepts in data mining and exploratory statistical to students and professional statisticians-both those working in and those working in a technological or capacity-who have a limited knowledge of data mining.

This book presents key statistical concepts by way of case studies, giving readers the benefit of learning from real problems and real data. Aided by a diverse range of statistical methods and techniques, readers will move from simple problems to complex problems. Through these case studies, authors Adelchi Azzalini and Bruno Scarpa explain exactly how statistical methods work; rather than relying on the “push the button” philosophy, they demonstrate how to use statistical tools to find the best solution to any given problem.

Case studies feature current topics highly relevant to data mining, such web page traffic; the segmentation of customers; selection of customers for direct mail commercial campaigns; fraud detection; and measurements of customer satisfaction. Appropriate for both advanced undergraduate and graduate students, this much-needed book will fill a gap between higher level books, which emphasize technical explanations, and lower level books, which assume no prior knowledge and do not explain the methodology behind the statistical operations.

Table of Contents

1. Introduction
2. A–B–
3. Optimism, Conflicts, and Trade-offs
4. Prediction of Quantitative Variables
5. Methods of Classification
6. Methods of Internal Analysis
Appendix A: Complements of and
Appendix B: Data Sets
Appendix C: Symbols and Acronyms

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