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Data Mining and Statistical Analysis Using SQL - John Lovett  Jr., Robert P. Trueblood

Data Mining and Statistical Analysis Using SQL

Buch | Softcover
410 Seiten
2001 | Softcover reprint of the original 1st ed.
Apress (Verlag)
978-1-893115-54-5 (ISBN)
CHF 67,35 inkl. MwSt
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!

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.

1 Basic Statistical Principles and Diagnostic Tree.- 2 Measures of Central Tendency and Dispersion.- 3 Goodness of Fit.- 4 Additional Tests of Hypothesis.- 5 Curve Fitting.- 6 Control Charting.- 7 Analysis of Experimental Designs.- 8 Time Series Analysis.- Appendix A Overview of Relational Database Structure and SQL.- Appendix B Statistical Tables.- Appendix C Tables of Statistical Distributions and Their Characteristics.- Appendix D Visual Basic Routines.

Erscheint lt. Verlag 18.9.2001
Zusatzinfo 151 Illustrations, black and white; XVI, 410 p. 151 illus.
Verlagsort Berkley
Sprache englisch
Maße 191 x 235 mm
Themenwelt Mathematik / Informatik Informatik Datenbanken
Mathematik / Informatik Informatik Programmiersprachen / -werkzeuge
Mathematik / Informatik Informatik Software Entwicklung
Informatik Theorie / Studium Compilerbau
Schlagworte Customer Relationship Management • Database Management • Data Mining • Data Warehouse • SQL • Statistics • Statistik
ISBN-10 1-893115-54-2 / 1893115542
ISBN-13 978-1-893115-54-5 / 9781893115545
Zustand Neuware
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