9781509305889

Microsoft Excel 2019 Data Analysis and Business Modeling

by
  • ISBN13:

    9781509305889

  • ISBN10:

    1509305882

  • Edition: 6th
  • Format: Paperback
  • Copyright: 2019-04-15
  • Publisher: Microsoft Press

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Supplemental Materials

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Summary

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 PowerQuery 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

Author Biography

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. 

Table of Contents

Previous Edition Table of Contents

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                   

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                    

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 duration of a project

Chapter 72 Making probability statements from forecasts

Chapter 73 Using the lognormal random variable to model stock prices

Chapter 74 Introduction to Monte Carlo simulation

Chapter 75 Calculating an optimal bid

Chapter 76 Simulating stock prices and asset-allocation modeling

Chapter 77 Fun and games: Simulating gambling and sporting-event probabilities

Chapter 78 Using resampling to analyze data

Chapter 79 Pricing stock options

Chapter 80 Determining customer value

Chapter 81 The economic order quantity inventory model

Chapter 82 Inventory modeling with uncertain demand

Chapter 83 Queuing theory: The mathematics of waiting in line

Chapter 84 Estimating a demand curve

Chapter 85 Pricing products by using tie-ins

Chapter 86 Pricing products by using subjectively determined demand

Chapter 87 Nonlinear pricing

Chapter 88 Array formulas and functions

Chapter 89 Recording macros

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