
Data Analysis and Data Mining
An Introduction
Oxford University Press Inc
1st Edition
Published on 31. May 2012
Book
Hardback
288 pages
978-0-19-976710-6 (ISBN)
Description
An introduction to statistical data mining, Data Analysis and Data Mining is both textbook and professional resource. Assuming only a basic knowledge of statistical reasoning, it presents core concepts in data mining and exploratory statistical models to students and professional statisticians-both those working in communications and those working in a technological or scientific 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.
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.
More details
Language
English
Place of publication
New York
United States
Target group
College/higher education
Advanced undergraduate and graduate students in statistics programs and professional statisticians who work in business-related areas.
Illustrations
110 b&w line
Dimensions
Height: 240 mm
Width: 161 mm
Thickness: 20 mm
Weight
602 gr
ISBN-13
978-0-19-976710-6 (9780199767106)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

E-Book
04/2012
1st Edition
OUP eBook
€94.99
Available for download

E-Book
03/2012
1st Edition
OUP eBook
€94.99
Available for download
Persons
Adelchi Azzalini is Professor of Statistics in the Department of Statistical Sciences at the University of Padua. He actively researches in statistical methodology and has maintained an interest in statistical applications.
Bruno Scarpa is Researcher in the Department of Statistical Sciences at the University of Padua. He previously worked as a statistician and data miner in marketing divisions of insurance and telecommunication companies.
Bruno Scarpa is Researcher in the Department of Statistical Sciences at the University of Padua. He previously worked as a statistician and data miner in marketing divisions of insurance and telecommunication companies.
Author
Professor of StatisticsProfessor of Statistics, University of Padua, Italy
ResearcherResearcher, University of Padua, Italy
Content
Preface ; 1 Introduction ; 2 A-B-C ; 3 Optimism, conflicts and trade-offs ; 4 Prediction of quantitative variables ; 5 Methods of classification ; 6 Methods of internal analysis ; A Complements of mathematics and statistics ; B Data-sets ; C Symbols and acronyms