Book Image

Data Analysis Using SQL and Excel - Second Edition

By : Gordon S. S. Linoff
Book Image

Data Analysis Using SQL and Excel - Second Edition

By: Gordon S. S. Linoff

Overview of this book

Data Analysis Using SQL and Excel, 2nd Edition shows you how to leverage the two most popular tools for data query and analysis—SQL and Excel—to perform sophisticated data analysis without the need for complex and expensive data mining tools. Written by a leading expert on business data mining, this book shows you how to extract useful business information from relational databases. You'll learn the fundamental techniques before moving into the "where" and "why" of each analysis, and then learn how to design and perform these analyses using SQL and Excel. Examples include SQL and Excel code, and the appendix shows how non-standard constructs are implemented in other major databases, including Oracle and IBM DB2/UDB. The companion website includes datasets and Excel spreadsheets, and the book provides hints, warnings, and technical asides to help you every step of the way. Data Analysis Using SQL and Excel, 2nd Edition shows you how to perform a wide range of sophisticated analyses using these simple tools, sparing you the significant expense of proprietary data mining tools like SAS.
Table of Contents (18 chapters)
Free Chapter
1
Foreword
17
EULA

Background on Survival Analysis

The origins of survival analysis can be traced back to a paper published in 1693 by Edmund Halley, as described in the aside “An Early History of Survival Analysis.” The techniques were developed further in the late 19th and 20th centuries, particularly for applications in social sciences, industrial process control, and medical research. These applications necessarily used a small amount of data because all data was collected by hand. A typical medical study, for instance, has dozens or hundreds of participants, rather than the multitudes of customers whose information is stored in today’s databases.

This section shows some examples of survival analysis without strictly defining terms such as hazard probabilities and survival. The examples start with life expectancy, then an explanation of survival in the medical realm, and finally give an example of hazard probabilities and how they shed light on customer behavior.