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Data Analysis Using SQL and Excel

Data Analysis Using SQL and Excel - Second Edition

By : Gordon S. S. Linoff
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Data Analysis Using SQL and Excel

Data Analysis Using SQL and Excel

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)
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1
Foreword
17
EULA

Measuring Goodness of Fit Using R2

How good is the best-fit line? Understanding how well a model works can be as important as building the model in the first place. Scatter plots of some data look a lot like a line; in such cases, the best-fit line fits the data quite well. In other cases, the data looks like a big blob, and the best-fit line is not very descriptive. The R2 value provides a measure to distinguish these situations.

The R2 Value

R2 measures how well the best-fit line fits the data. When the line does not fit the data at all, the value is zero. When the line is a perfect fit, the value is one.

The best way to understand this measure is to see it in action. Figure 12-92 value of 0.9; the two on the bottom have an R2 value of 0.1. The two on the left have positive correlation, and the two on the right have negative correlation.

Two graphs on Positive, Negative correlation have increasing and decreasing slanting lines respectively with scattered points for R^2 = 0.9, 0.1. Line more sloping for former.

Figure 12.9: The four examples here show the different scenarios of positive and negative correlation among the data points, and examples with...

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Data Analysis Using SQL and Excel
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