# Microsoft Excel 2019 Data Analysis and Business Modeling, 6th Edition

- Length: 880 pages
- Edition: 6
- Language: English
- Publisher: Microsoft Press
- Publication Date: 2019-04-25
- ISBN-10: 1509305882
- ISBN-13: 9781509305889

## Book Description

Master business modeling and analysis techniques with Microsoft Excel 2019 and Office 365 and transform data into bottom-line results. Written by award-winning educator Wayne Winston, this hands-on, scenario-focused guide helps you use Excel to ask the right questions and get accurate, actionable answers. New coverage ranges from Power Query/Get & Transform to Office 365 Geography and Stock data types. Practice with more than 800 problems, many based on actual challenges faced by working analysts.

Solve real business problems with Excel—and build your competitive advantage:

- Quickly transition from Excel basics to sophisticated analytics
- Use PowerQuery or Get & Transform to connect, combine, and refine data sources
- Leverage Office 365’s new Geography and Stock data types and six new functions
- Illuminate insights from geographic and temporal data with 3D Maps
- Summarize data with pivot tables, descriptive statistics, histograms, and Pareto charts
- Use Excel trend curves, multiple regression, and exponential smoothing
- Delve into key financial, statistical, and time functions
- Master all of Excel’s great charts
- Quickly create forecasts from historical time-based data
- Use Solver to optimize product mix, logistics, work schedules, and investments—and even rate sports teams
- Run Monte Carlo simulations on stock prices and bidding models
- Learn about basic probability and Bayes’ Theorem
- Use the Data Model and Power Pivot to effectively build and use relational data sources inside an Excel workbook
- Automate repetitive analytics tasks by using macros

## Table of Contents

Chapter 1. Basic worksheet modeling

Chapter 2. Range names

Chapter 3. Lookup functions

Chapter 4. The INDEX function

Chapter 5. The MATCH function

Chapter 6. Text functions and Flash Fill

Chapter 7. Dates and date functions

Chapter 8. NPV and XNPV functions

Chapter 9. IRR, XIRR, and MIRR functions

Chapter 10. More Excel financial functions

Chapter 11. Circular references

Chapter 12. IF, IFERROR, IFS, CHOOSE, and SWITCH functions

Chapter 13. Time and time functions

Chapter 14. The Paste Special command

Chapter 15. Three-dimensional formulas and hyperlinks

Chapter 16. The auditing tool and the Inquire add-in

Chapter 17. Sensitivity analysis with data tables

Chapter 18. The Goal Seek command

Chapter 19. Using the Scenario Manager for sensitivity analysis

Chapter 20. The COUNTIF, COUNTIFS, COUNT, COUNTA, and COUNTBLANK functions

Chapter 21. The SUMIF, AVERAGEIF, SUMIFS, AVERAGEIFS, MAXIFS, and MINIFS functions

Chapter 22. The OFFSET function

Chapter 23. The INDIRECT function

Chapter 24. Conditional formatting

Chapter 25. Sorting in Excel

Chapter 26. Excel tables and table slicers

Chapter 27. Spin buttons, scrollbars, option buttons, check boxes, combo boxes, and group list boxes

Chapter 28. The analytics revolution

Chapter 29. An introduction to optimization with Excel Solver

Chapter 30. Using Solver to determine the optimal product mix

Chapter 31. Using Solver to schedule your workforce

Chapter 32. Using Solver to solve transportation or distribution problems

Chapter 33. Using Solver for capital budgeting

Chapter 34. Using Solver for financial planning

Chapter 35. Using Solver to rate sports teams

Chapter 36. Warehouse location and the GRG Multistart and Evolutionary Solver engines

Chapter 37. Penalties and the Evolutionary Solver

Chapter 38. The traveling salesperson problem

Chapter 39. Importing data from a text file or document

Chapter 40. Get & Transform

Chapter 41. Geography and Stock data types

Chapter 42. Validating data

Chapter 43. Summarizing data by using histograms and Pareto charts

Chapter 44. Summarizing data by using descriptive statistics

Chapter 45. Using pivot tables and slicers to describe data

Chapter 46. The Data Model

Chapter 47. Power Pivot

Chapter 48. Filled and 3D Power Maps

Chapter 49. Sparklines

Chapter 50. Summarizing data with database statistical functions

Chapter 51. Filtering data and removing duplicates

Chapter 52. Consolidating data

Chapter 53. Creating subtotals

Chapter 54. Charting tricks

Chapter 55. Estimating straight-line relationships

Chapter 56. Modeling exponential growth

Chapter 57. The power curve

Chapter 58. Using correlations to summarize relationships

Chapter 59. Introduction to multiple regression

Chapter 60. Incorporating qualitative factors into multiple regression

Chapter 61. Modeling nonlinearities and interactions

Chapter 62. Analysis of variance: One-way ANOVA

Chapter 63. Randomized blocks and two-way ANOVA

Chapter 64. Using moving averages to understand time series

Chapter 65. Winters method and the Forecast Sheet

Chapter 66. Ratio-to-moving-average forecast method

Chapter 67. Forecasting in the presence of special events

Chapter 68. An introduction to probability

Chapter 69. An introduction to random variables

Chapter 70. The binomial, hypergeometric, and negative binomial random variables

Chapter 71. The Poisson and exponential random variable

Chapter 72. The normal random variable and Z-scores

Chapter 73. Weibull and beta distributions: Modeling machine life and duration of a project

Chapter 74. Making probability statements from forecasts

Chapter 75. Using the lognormal random variable to model stock prices

Chapter 76. Importing historical stock data into Excel

Chapter 77. Introduction to Monte Carlo simulation

Chapter 78. Calculating an optimal bid

Chapter 79. Simulating stock prices and asset-allocation modeling

Chapter 80. Fun and games: Simulating gambling and sporting event probabilities

Chapter 81. Using resampling to analyze data

Chapter 82. Pricing stock options

Chapter 83. Determining customer value

Chapter 84. The economic order quantity inventory model

Chapter 85. Inventory modeling with uncertain demand

Chapter 86. Queuing theory: The mathematics of waiting in line

Chapter 87. Estimating a demand curve

Chapter 88. Pricing products by using tie-ins

Chapter 89. Pricing products by using subjectively determined demand

Chapter 90. Nonlinear pricing

Chapter 91. Array formulas and functions

Chapter 92. Recording macros

Chapter 93. Advanced sensitivity analysis

## About The Author

##### Wayne Winston

Wayne L. Winston is a professor of Decision Sciences at Indiana University's Kelley School of Business and has earned numerous MBA teaching awards. For 20+ years, he has taught clients at Fortune 500 companies how to use Excel to make smarter business decisions. Wayne and his business partner Jeff Sagarin developed the player-statistics tracking and rating system used by the Dallas Mavericks professional basketball team. He is also a two time Jeopardy! Champion.