Microsoft Excel 2019 Data Analysis and Business Modeling
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Microsoft Excel 2019 Data Analysis and Business Modeling: (Business Skills)

Microsoft Excel 2019 Data Analysis and Business Modeling: (Business Skills)


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About the Book

Transform data into bottom-line results Master business modeling and analysis techniques with Microsoft Excel 2019, and transform data into bottom-line results. Written by award-winning educator Wayne Winston, this hands-on, scenario-focused guide shows you how to use the latest Excel tools to integrate data from multiple tables and how to effectively build a relational data source inside an Excel workbook.

Table of Contents:
1 Basic worksheet modeling 2 Range names 3 Lookup functions 4 The INDEX function 5 The MATCH function 6 Text functions and Flash Fill 7 Dates and date functions 8 Evaluating investments by using net present value criteria 9 IRR, XIRR, and MIRR functions 10 More Excel financial functions 11 Circular references 12 IF, IFERROR, IFS, CHOOSE, and SWITCH functions 13 Time and time functions 14 The Paste Special command 15 Three-dimensional formulas and hyperlinks 16 The auditing tool and the Inquire add-in 17 Sensitivity analysis with data tables 18 The Goal Seek command 19 Using the Scenario Manager for sensitivity analysis 20 The COUNTIF, COUNTIFS, COUNT, COUNTA, and COUNTBLANK functions 21 The SUMIF, AVERAGEIF, SUMIFS, AVERAGEIFS, MAXIFS, and MINIFS functions 22 The OFFSET function 23 The INDIRECT function 24 Conditional formatting 25 Sorting in Excel 26 Excel tables and table slicers 27 Spin buttons, scrollbars, option buttons, check boxes, combo boxes, and group list boxes 28 The analytics revolution 29 An introduction to optimization with Excel Solver 30 Using Solver to determine the optimal product mix 31 Using Solver to schedule your workforce 32 Using Solver to solve transportation or distribution problems 33 Using Solver for capital budgeting 34 Using Solver for financial planning 35 Using Solver to rate sports teams 36 Warehouse location and the GRG Multistart and Evolutionary Solver engines 37 Penalties and the Evolutionary Solver 38 The traveling salesperson problem 39 Importing data from a text file or document 40 Get & Transform (or s/b Get & Transform?) 41 Geography and Stock data types 42 Validating data 43 Summarizing data by using histograms and Pareto charts 44 Summarizing data by using descriptive statistics 45 Using pivot tables and slicers to describe data 46 The Data Model 47 Power Pivot 48 Filled and 3D Power Maps 49 Sparklines 50 Summarizing data with database statistical functions 51 Filtering data and removing duplicates 52 Consolidating data 53 Creating subtotals 54 Charting tricks 55 Estimating straight-line relationships 56 Modeling exponential growth 57 The power curve 58 Using correlations to summarize relationships 59 Introduction to multiple regression 60 Incorporating qualitative factors into multiple regression 61 Modeling nonlinearities and interactions 62 Analysis of variance: One-way ANOVA 63 Randomized blocks and two-way ANOVA 64 Using moving averages to understand time series 65 Winters method and the Forecast Sheet 66 Ratio-to-moving-average forecast method 67 Forecasting in the presence of special events 68 Introduction to Probability 69 An introduction to random variables 70 The binomial, hypergeometric, and negative binomial random variables 71 The Poisson and exponential random variables 72 The normal random variable and Z-scores 73 Weibull and beta distributions: Modeling machine life and project duration 74 Making probability statements from forecasts 75 Using the lognormal random variable to model stock prices 76 Importing Historical stock data into Excel 77 Introduction to Monte Carlo simulation 78 Calculating an optimal bid 79 Simulating stock prices and asset-allocation modeling 80 Fun and games: Simulating gambling and sporting event probabilities 81 Using resampling to analyze data  82 Pricing stock options 83 Determining customer value 84 The economic order quantity inventory model 85 Inventory modeling with uncertain demand 86 Queueing theory: The mathematics of waiting in line 87 Estimating a demand curve 88 Pricing products by using tie-ins 89 Pricing products by using subjectively determined demand 90 Nonlinear pricing 91 Array formulas and functions 92 Recording macros 93 Advanced Sensitivity Analysis

About the Author :
Wayne L. Winston is Professor Emeritus of Decision Sciences at the Indiana University School of Business. He has also taught at the University of Houston and Wake Forest. He has won more than 40 teaching awards and taught Excel modeling and analytics at many Fortune 500 companies, accounting firms, the U.S. Army, and the U.S. Navy.


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Product Details
  • ISBN-13: 9781509305889
  • Publisher: Microsoft Press,U.S.
  • Publisher Imprint: Microsoft Press
  • Height: 231 mm
  • No of Pages: 880
  • Series Title: Business Skills
  • Weight: 1340 gr
  • ISBN-10: 1509305882
  • Publisher Date: 22 Apr 2019
  • Binding: Paperback
  • Language: English
  • Returnable: Y
  • Spine Width: 41 mm
  • Width: 188 mm


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Microsoft Excel 2019 Data Analysis and Business Modeling: (Business Skills)
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