Microsoft Excel 2019 Data Analysis and Business Modeling (häftad)
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Häftad (Paperback)
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Microsoft Press
231 x 185 x 43 mm
1430 g
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Microsoft Excel 2019 Data Analysis and Business Modeling (häftad)

Microsoft Excel 2019 Data Analysis and Business Modeling

Häftad Engelska, 2019-04-15
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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 Exceland 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 365s 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 Excels great charts 
  • Quickly create forecasts from historical time-based data 
  • Use Solver to optimize product mix, logistics, work schedules, and investmentsand 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
Excel; Office 2016; Windows 10; data analysis; business modeling; PivotTables; Descriptive Statistics; predictive analytics
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Fler böcker av Wayne Winston

Övrig information

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 Chapter20The 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 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 Chapter 68 The binomial, hypergeometric, and negative binomial random variables Chapter 69 The Poisson and exponential random variable Chapter 70 The normal random variable and Z-scores Chapter 71 Weibull and beta distributions: Modeling machine life and duratio