Book description
Master business modeling and analysis techniques with Microsoft Excel 2019, 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.
Table of contents
- Cover Page
- Title Page
- Copyright Page
- Dedication Page
- Contents at a glance
- Contents
- About the author
- Introduction
- 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
- Index
- Code Snippets
Product information
- Title: Microsoft Excel 2019 Data Analysis and Business Modeling, 6th Edition
- Author(s):
- Release date: April 2019
- Publisher(s): Microsoft Press
- ISBN: 9781509306091
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