Data Mining & Statistical Analysis Using SQL (Paperback)

~ Jr., John N. Lovett (Author), Robert P. Trueblood (Author), John N. Lovett Jr. (Author)
Key Phrases: actual gross sales, forecast error, job stress, Three Way, Sample Number, Life Expectancy (more...)

Editorial Reviews

Amazon.com Review

Data Mining and Statistical Analysis Using SQL concerns itself with the interface between applied mathematics--the discipline of statistical analysis--and really applied mathematics in the form of Structured Query Language (SQL) code that carries out such analysis. It's a subject that deserves careful coverage in a book, and the authors of this one--both working analysts with distinguished academic backgrounds--have done great work. If you're faced with a need to derive meaning from large quantities of data (from retail sales, industrial processes, or even scientific observations), and canned analysis tools aren't cutting it for you, take time to study what Robert Trueblood and John Lovett have to say.

Though some background in statistics will help you pick up on what Trueblood and Lovett have written, a low-level university class (even one far in your past) should be enough. Their approach to all of the analysis techniques they teach is to explain terms and concepts with prose, then with graphs, then with formulas. Then, they translate the formulas into SQL queries for Microsoft Access and show variations on the code that yield differently tweaked results. Finally, T-SQL source code (for Microsoft SQL Server 2000) is listed, though most readers will prefer to grab this code from the book's companion Web site. Additional coverage of graphics would make this book better, but in its present state it's great reading for people who want to interpret their mountains of data. --David Wall

Topics covered: Statistical analysis as a set of mathematical tools that may be implemented in Structured Query Language (SQL), specifically SQL variants for Microsoft database products. Chapters explain how to use hypothesis testing, curve fitting, scatter plots, measurements of central tendency, and regression analysis to spot significant characteristics of data.

Product Description

<p>This book is not just another theoretical text about statistics or data mining. No, instead it is aimed for you DBAs who want to use SQL, or bolster your understanding of statistics to support data mining and customer relationship management analytics. <p>

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 VB procedure using SQL. Chapter contents include formulas, graphs, charts, tables, data mining techniques, and more!

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Product Details

• Paperback: 250 pages
• Publisher: Apress; 1 edition (October 15, 2001)
• Language: English
• ISBN-10: 1893115542
• ISBN-13: 978-1893115545
• Product Dimensions: 9.1 x 7.9 x 1.1 inches
• Shipping Weight: 1.5 pounds (View shipping rates and policies)
• Average Customer Review: 3.0 out of 5 stars  See all reviews (6 customer reviews)
• Amazon.com Sales Rank: #1,270,459 in Books (See Bestsellers in Books)

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Customer Reviews

Most Helpful Customer Reviews

14 of 14 people found the following review helpful:

3.0 out of 5 stars Should be called "Basic Statistical Analysis Using SQL", June 6, 2002

By	Larry Bahney "WharfRat" (Canton, OH United States) - See all my reviews (REAL NAME)

My perspective is that I do not consider basic statistics a part of Data Mining. By basic statistics, I mean ANOVA, regression, etc. Therefore, I feel the title is misleading. Only basic statistical analysis is shown using SQL. Data Mining techniques are not covered.

As far as statistical analysis .... The Design of Experiments chapter does not cover replicated ANOVA, and does not even mention factorial designs. The Time Series chapter does not cover autoregressive-moving average models.

If you want a book that implements some of Excel's Analysis Tools routines in SQL, then this book is for you. If you want an introduction to data mining techniques, look elsewhere.

10 of 10 people found the following review helpful:

3.0 out of 5 stars Data Mining and Statistical Analysis Using SQL, September 16, 2001

By	John Jiang "johnjjiang" (Shelton, CT United States) - See all my reviews

This would be a good book for Statistical Analysis using SQL, but it lacks the other side of data mining-data visualization. I hope the authors would include some non-statistical techniques of data mining in their future edition.

At the meanwhile, reader may read other books, such as C. Westphal's Data Mining Solutions, for non-statistical data visualization techniques.

10 of 12 people found the following review helpful:

1.0 out of 5 stars Liar, liar, pants on fire--no data mining in this book, November 19, 2002

By	Phillip I. Good (Huntington Beach, CA United States) - See all my reviews (REAL NAME)

This is yet another introductory statistics text--a particularly old-fashioned one. The words "Data Mining" in the title are toitally misleading and I'm sorry I borrowed it. It is useless as a text book as it has nothing on resampling methods, the bootstrap and permutation tests.