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## Book Description

As one of the most widely used desktop applications ever created, Excel is familiar to just about everyone with a computer and a keyboard. Yet most of us don't know the full extent of what Excel can do, mostly because of its recent growth in power, versatility, and complexity. The truth is that there are many ways Excel can help make your job easier-beyond calculating sums and averages in a standard spreadsheet.

Analyzing Business Data with Excel shows you how to solve real-world business problems by taking Excel's data analysis features to the max. Rather than focusing on individual Excel functions and features, the book keys directly on the needs of business users. Most of the chapters start with a business problem or question, and then show you how to create pointed spreadsheets that address common data analysis issues.

Aimed primarily at experienced Excel users, the book doesn't spend much time on the basics. After introducing some necessary general tools, it quickly moves into more specific problem areas, such as the following:

• Statistics

• Pivot tables

• Modeling

• Measuring quality

• Monitoring complex systems

• Queuing

• Optimizing

• Importing data

If you feel as though you're getting shortchanged by your overall application of Excel, Analyzing Business Data with Excel is just the antidote. It addresses the growing Excel data analysis market head on. Accountants, managers, analysts, engineers, and supervisors-one and all-will learn how to turn Excel functionality into actual solutions for the business problems that confront them.

1. Analyzing Business Data with Excel
2. SPECIAL OFFER: Upgrade this ebook with O’Reilly
3. A Note Regarding Supplemental Files
4. Preface
1. Who Should Read This Book
2. What's in This Book
3. How to Use This Book Effectively
4. Sample Code
5. Using Code Examples
7. Safari® Enabled
8. Acknowledgments
5. 1. Excel and Statistics
1. 1.1. Array Formulas
3. 1.3. Statistical Functions
1. 1.3.1. The Average
2. 1.3.2. Changes in the Average
3. 1.3.3. Distributions
4. 1.3.4. Correlation
6. 2. Pivot Tables and Problem Solving
1. 2.1. Pivot Table Basics
2. 2.2. Changing the Data
3. 2.3. Pivot Table Options
1. 3.1. The Procedure
1. 3.1.1. Data
2. 3.1.2. Predictions
3. 3.1.3. Determine the Confidence Interval
4. 3.1.4. Manage Anomalies
2. 3.2. Building an Application
8. 4. Modeling
9. 5. Measuring Quality
1. 5.1. Statistical Process Control
2. 5.2. Running the Application
3. 5.3. Application Design
1. 5.3.1. The Data Sheet
2. 5.3.2. The Workarea Sheet
3. 5.3.3. The Controls on the Display Sheet
4. 5.3.4. Linking the Workarea Sheet to the Data Sheet
5. 5.3.5. The Display Sheet
4. 5.4. Customizing the Application
10. 6. Monitoring Complex Systems
1. 6.1. The Application
2. 6.2. The Data
3. 6.3. Settings
4. 6.4. Workarea
5. 6.5. Macros
11. 7. Queuing
1. 7.1. The Data
2. 7.2. The Application
3. 7.3. The Logic
12. 8. Custom Queuing Presentation
13. 9. Optimizing
1. 9.1. Goal Seek
2. 9.2. The Solver
14. 10. Importing Data
1. 10.1. Text Files
2. 10.2. Databases
3. 10.3. XML
15. 11. The Trouble with Data
16. 12. Effective Display Techniques
1. 12.1. Respect the Information and the Audience
2. 12.2. Large Worksheets
3. 12.3. Charts
4. 12.4. Pictures and Other Objects
5. 12.5. Complexity
6. 12.6. Repeated Elements
7. 12.7. Information Density
8. 12.8. Emphasis and Focus
17. Index