Microsoft Excel data analysis and business modeling

Well known consultant, statistician, and business professor Wayne Winston teaches by example the best ways to use Microsoft Excel for data analysis, modeling, and decision making within real-world business scenarios

1. Range Names -- 2. Natural Language Range Names -- 3. Lookup Functions -- 4. The INDEX Function -- 5. The MATCH Function -- 6. Text Functions -- 7. Dates and Date Functions -- 8. Evaluating Investments with Net Present Value Criteria -- 9. Internal Rate of Return -- 10. Functions for Personal Financial Decisions: The PV, FV, PMT, PPMT, and IPMT Functions -- 11. Circular References -- 12. IF Statements -- 13. The Paste Special Command -- 14. The Auditing Tool -- 15. Sensitivity Analysis with Data Tables -- 16. The Goal Seek Command -- 17. Using the Scenario Manager for Sensitivity Analysis -- 18. Creating and Using Spinners for Sensitivity Analysis -- 19. The COUNTIF, COUNT, COUNTA, and COUNTBLANK Functions -- 20. The SUMIF Function -- 21. The OFFSET Function -- 22. The INDIRECT Function -- 23. Conditional Formatting -- 24. An Introduction to Optimization with the Excel Solver -- 25. Using Solver to Determine the Optimal Product Mix -- 26. Using Solver to Solve Transportation or Distribution Problems -- 27. Using Solver to Schedule Your Workforce -- 28. Using Solver for Capital Budgeting -- 29. Using Solver for Financial Planning -- 30. Using Solver to Rate Sports Teams -- 31. Importing Text or Microsoft Word Data into Excel -- 32. Importing Data from the Web into Excel -- 33. Validating Data -- 34. Summarizing Data with Histograms -- 35. Summarizing Data with Descriptive Statistics -- 36. Using PivotTables to Describe Data -- 37. Summarizing Data with Database Statistical Functions -- 38. Filtering Data -- 39. Consolidating Data -- 40. Creating Subtotals -- 41. Estimating Straight Line Relationships -- 42. Modeling Exponential Growth -- 43. The Power Curve -- 44. Using Correlations to Summarize Relationships -- 45. Introduction to Multiple Regression -- 46. Incorporating Qualitative Factors into Multiple Regression -- 47. Modeling Nonlinearities and Interactions -- 48. Analysis of Variance: One-Way ANOVA -- 49. Randomized Blocks and Two-Way ANOVA -- 50. Using Moving Averages to Understand Time Series -- 51. Forecasting with Moving Averages -- 52. Forecasting in the Presence of Special Events -- 53. An Introduction to Random Variables -- 54. The Binomial and Hypergeometric Random Variables -- 55. The Poisson and Exponential Random Variable -- 56. The Normal Random Variable -- 57. Weibull and Beta Distributions: Modeling Machine Life and Duration of a Project -- 58. Introduction to Monte Carlo Simulation -- 59. Calculating an Optimal Bid -- 60. Simulating Stock Prices and Asset Allocation Modeling -- 61. Fun and Games: Simulating Gambling and Sporting Event Probabilities -- 62. Using Resampling to Analyze Data -- 63. Pricing Stock Options -- 64. Determining Customer Value -- 65. The Economic Order Quantity Inventory Model -- 66. Determining the Reorder Point: How Low Should I Let My Inventory Level Go Before I Reorder? -- 67. Queuing Theory: The Mathematics of Waiting in Line -- 68. Estimating a Demand Curve -- 69. Pricing Products with Tie-ins -- 70. Pricing Products Using Subjectively Determined Demand -- 71. Nonlinear Pricing -- 72. Array Formulas and Functions -- 73. Picking Your Fantasy Football Team

Notes

tight binding on some pages

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