# Microsoft Excel 2013: Data Analysis and Business Modeling

Master business modeling and analysis techniques with Microsoft Excel 2013, and transform data into bottom-line results. Written by award-winning educator Wayne Winston, this hands-on, scenario-focused guide shows you how to use the latest Excel tools to integrate data from multiple tables—and how to effectively build a relational data source inside an Excel workbook.

Solve real business problems with Excel—and sharpen your edge

- Summarize data with PivotTables and Descriptive Statistics
- Explore new trends in predictive and prescriptive analytics
- Use Excel Trend Curves, multiple regression, and exponential smoothing
- Master advanced Excel functions such as OFFSET and INDIRECT
- Delve into key financial, statistical, and time functions
- Make your charts more effective with the Power View tool
- Tame complex optimization problems with Excel Solver
- Run Monte Carlo simulations on stock prices and bidding models
- Apply important modeling tools such as the Inquire add-in

**Table of Contents**

Chapter 1. Range names

Chapter 2. Lookup functions

Chapter 3. INDEX function

Chapter 4. MATCH function

Chapter 5. Text functions

Chapter 6. Dates and date functions

Chapter 7. Evaluating investments by using net present value criteria

Chapter 8. Internal rate of return

Chapter 9. More Excel financial functions

Chapter 10. Circular references

Chapter 11. IF statements

Chapter 12. Time and time functions

Chapter 13. The Paste Special command

Chapter 14. Three-dimensional formulas

Chapter 15. The Auditing tool and Inquire add-in

Chapter 16. Sensitivity analysis with data tables

Chapter 17. The Goal Seek command

Chapter 18. Using the Scenario Manager for sensitivity analysis

Chapter 19. The COUNTIF, COUNTIFS, COUNT, COUNTA, and COUNTBLANK functions

Chapter 20. The SUMIF, AVERAGEIF, SUMIFS, and AVERAGEIFS functions

Chapter 21. The OFFSET function

Chapter 22. The INDIRECT function

Chapter 23. Conditional formatting

Chapter 24. Sorting in Excel

Chapter 25. Tables

Chapter 26. Spinner buttons, scroll bars, option buttons, check boxes, combo boxes, and group list boxes

Chapter 27. The analytics revolution

Chapter 28. Introducing optimization with Excel Solver

Chapter 29. Using Solver to determine the optimal product mix

Chapter 30. Using Solver to schedule your workforce

Chapter 31. Using Solver to solve transportation or distribution problems

Chapter 32. Using Solver for capital budgeting

Chapter 33. Using Solver for financial planning

Chapter 34. Using Solver to rate sports teams

Chapter 35. Warehouse location and the GRG Multistart and Evolutionary Solver engines

Chapter 36. Penalties and the Evolutionary Solver

Chapter 37. The traveling salesperson problem

Chapter 38. Importing data from a text file or document

Chapter 39. Importing data from the Internet

Chapter 40. Validating data

Chapter 41. Summarizing data by using histograms

Chapter 42. Summarizing data by using descriptive statistics

Chapter 43. Using PivotTables and slicers to describe data

Chapter 44. The Data Model

Chapter 45. PowerPivot

Chapter 46. Power View

Chapter 47. Sparklines

Chapter 48. Summarizing data with database statistical functions

Chapter 49. Filtering data and removing duplicates

Chapter 50. Consolidating data

Chapter 51. Creating subtotals

Chapter 52. Charting tricks

Chapter 53. Estimating straight-line relationships

Chapter 54. Modeling exponential growth

Chapter 55. The power curve

Chapter 56. Using correlations to summarize relationships

Chapter 57. Introduction to multiple regression

Chapter 58. Incorporating qualitative factors into multiple regression

Chapter 59. Modeling nonlinearities and interactions

Chapter 60. Analysis of variance: one-way ANOVA

Chapter 61. Randomized blocks and two-way ANOVA

Chapter 62. Using moving averages to understand time series

Chapter 63. Winters’s method

Chapter 64. Ratio-to-moving-average forecast method

Chapter 65. Forecasting in the presence of special events

Chapter 66. An introduction to random variables

Chapter 67. The binomial, hypergeometric, and negative binomial random variables

Chapter 68. The Poisson and exponential random variable

Chapter 69. The normal random variable

Chapter 70. Weibull and beta distributions: modeling machine life and duration of a project

Chapter 71. Making probability statements from forecasts

Chapter 72. Using the lognormal random variable to model stock prices

Chapter 73. Introduction to Monte Carlo simulation

Chapter 74. Calculating an optimal bid

Chapter 75. Simulating stock prices and asset allocation modeling

Chapter 76. Fun and games: simulating gambling and sporting event probabilities

Chapter 77. Using resampling to analyze data

Chapter 78. Pricing stock options

Chapter 79. Determining customer value

Chapter 80. The economic order quantity inventory model

Chapter 81. Inventory modeling with uncertain demand

Chapter 82. Queuing theory: the mathematics of waiting in line

Chapter 83. Estimating a demand curve

Chapter 84. Pricing products by using tie-ins

Chapter 85. Pricing products by using subjectively determined demand

Chapter 86. Nonlinear pricing

Chapter 87. Array formulas and functions

### Book Details

**Paperback:**888 pages**Publisher:**Microsoft Press (January 2014)**Language:**English**ISBN-10:**0735669139**ISBN-13:**978-0735669130