Data Mining and Statistical Analysis Using SQL - Lovett, John; Trueblood, Robert P.
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This book is not just another theoretical text on statistics or data mining. Instead, it's designed for database administrators who want to buttress their understanding of statistics to support data mining and customer relationship management analytics and who want to use Structured Query Language (SQL). Each chapter is independent and self-contained with examples tailored to business applications. Each analysis technique is expressed in a mathematical format that lends itself to coding either as a database query or as a Visual Basic procedure using SQL. Each chapter includes: formulas (how to…mehr

Produktbeschreibung
This book is not just another theoretical text on statistics or data mining. Instead, it's designed for database administrators who want to buttress their understanding of statistics to support data mining and customer relationship management analytics and who want to use Structured Query Language (SQL). Each chapter is independent and self-contained with examples tailored to business applications. Each analysis technique is expressed in a mathematical format that lends itself to coding either as a database query or as a Visual Basic procedure using SQL. Each chapter includes: formulas (how to perform the required analysis, numerical example using data from a database, data visualization and presentation options (graphs, charts, tables), SQL procedures for extracting the desired results, and data mining techniques.
  • Produktdetails
  • Verlag: APRESS / Apress
  • Softcover reprint of the original 1st ed
  • Seitenzahl: 432
  • Erscheinungstermin: 18. September 2001
  • Englisch
  • Abmessung: 235mm x 191mm x 23mm
  • Gewicht: 799g
  • ISBN-13: 9781893115545
  • ISBN-10: 1893115542
  • Artikelnr.: 09978387
Autorenporträt
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.