DATA ANALYSIS & DATA MINING C

1. Auflage 2018
ISBN: 978-0-19-976710-6
Verlag: ACADEMIC

Buch, Englisch, 288 Seiten, Format (B × H): 161 mm x 240 mm, Gewicht: 602 g

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.

Zielgruppe

Advanced undergraduate and graduate students in statistics programs and professional statisticians who work in business-related areas.

Autoren/Hrsg.

Azzalini

Azzalini, Adelchi

Scarpa, Bruno

Fachgebiete

• Mathematik | Informatik EDV | Informatik Business Application Mathematische & Statistische Software
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Datenanalyse, Datenverarbeitung
• Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik
• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining

Inhaltsverzeichnis

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

Über Autor(innen)

Azzalini, Adelchi
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.

Scarpa, Bruno
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.