Microsoft Excel 2019 Data Analysis and Business Modeling

Wayne L. Winston is Professor Emeritus of Decision Sciences at Indiana University’s Kelley School of Business, where he won 40+ teaching awards. He developed spreadsheet modeling coursework for Harvard Business School Publishing, and has taught or consulted on using Excel to improve decision-making at Microsoft, Cisco, Morgan Stanley, Pfizer, Verizon, the U.S. Navy, U.S. Army, and many other organizations. A two-time Jeopardy! Champion, he co-developed the Dallas Mavericks’ player tracking and rating system.

• Chapter 1 Basic spreadsheet modeling Chapter 2 Range names Chapter 3 Lookup functions Chapter 4 The INDEX function Chapter 5 The MATCH function Chapter 6 Text functions Chapter 7 Dates and date functions Chapter 8 Evaluating investment by using net present value criteria Chapter 9 Internal rate of return Chapter 10 More Excel financial functions Chapter 11 Circular references Chapter 12 IF statements Chapter 13 Time and time functions Chapter 14 The Paste Special command Chapter 15 Three-dimensional formulas and hyperlinks Chapter 16 The auditing tool 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, and AVERAGEIFS functions Chapter 22 The OFFSET function Chapter 23 The INDIRECT function Chapter 24 Conditional formatting Chapter 25 Sorting in Excel Chapter 26 Tables Chapter 27 Spin buttons, scroll bars, 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 Validating data Chapter 41 Summarizing data by using histograms and Pareto charts Chapter 42 Summarizing data by using descriptive statistics Chapter 43 Using PivotTables and slicers to describe data Chapter 44 The Data Model Chapter 45 Power Pivot Chapter 46 Power View and 3D Maps 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 method Chapter 64 Ratio-to-moving-average forecast method Chapter 65 Forecasting in the presence of special events Chapter 66 An introduction to probability Chapter 67 An introduction to random variables Chap