Data Mining & Statistical Analysis Using SQL
Jr., John N. Lovett, John N. Lovett
This book isn't designed to be just another theoretical text on statistics or data mining. Instead, it's aimed at DBAs, database administrators, who want to buttress their understanding of statistics to support data mining and customer relationship management analytics, and who want to use SQL, Structured Query Language.
Each chapter is independent and self-contained with examples that are tailored to business applications. Each analysis technique will be 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 will include the following:
- 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
- Data mining techniques
- Separate database
This book is a perfect supplemental resource for a statistics course.
- Chapter 1: Diagnostic Tree: How to approach your data.
- Chapter 2: Measures of Central Tendency and Dispersion
- Chapter 3: Goodness of Fit
- Chapter 4: Additional Tests of Hypothesis
- Chapter 5: Curve Fitting
- Chapter 6: Control Charting
- Chapter 7: Analysis of Variance
- Chapter 8: Time Series Analysis
- Overview of Relational Databases and SQL
- Statistical Tables Referenced In This Book
- Various Statistical Distributions
- Visual Basic Routines For Performing Statistical Calculations