MICROSOFT EXCEL 2019: DATA ANALYSIS&BUSINESS MODEL

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 Power Query 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. Contents: 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