Data Mining and Statistical Analysis Using SQL

John Lovett

ISBN 10: 1893115542 / ISBN 13: 9781893115545

Published by APress, 2001

About this Item

Where to Start xi Introduction WITH THE EXPLOSION IN computer technology during the past 30 years, there has been an accompanying proliferation of data. In many cases, however, companies have stacks of printed data or electronic databases that are of little use to them. This is often because those who could benefit the most from this information lack experience using the tools and techniques that could help them extract knowledge from the numbers. Now, more and more databases are also placed on the Internet. In fact, at no other time in history has more information been accessible to so many people. But how can it help us? Access to this information is important because data collected in the past may be used to predict future trends or to characterize a population from which a sample has been extracted. For example, a sample poll among 1,000 voters is often used to predict the outcome of an election. The latest computer-age term for this exercise is data min- ing. Statistics is the science (and art) of mining or analyzing such data. Like lawyers and physicians, statisticians have traditionally insulated themselves from the masses by using jargon and Greek symbols, thereby helping to ensure the need for their services.

Seller Inventory # CIN1893115542G

Bibliographic Details

• Title: Data Mining and Statistical Analysis Using SQL
• Publisher: APress
• Publication Date: 2001
• Language: English
• ISBN 10: 1893115542
• ISBN 13: 9781893115545
• Binding: Paperback
• Condition: Good

About this title

Synopsis

This book is not just another theoretical text about statistics or data mining. No, instead it is aimed for database administrators who want to use SQL or bolster their understanding of statistics to support data mining and customer relationship management analytics.

Each chapter is self-contained, with examples tailored to real business applications. And each analysis technique will be expressed in a mathematical format for coding as either a database query or a Visual Basic procedure using SQL. Chapter contents include formulas, graphs, charts, tables, data mining techniques, and more!

About the Author

John N. Lovett, Jr. is a senior engineering consultant at QuantiTech, Inc. and co-owner, with his anthropologist/archaeologist wife, Jane, of Falls Mill and Museum in Belvedere, Tennessee. He has a Ph.D. in industrial engineering, a master's degree in operations research, and a bachelor's degree in mathematics.