Microsoft Excel Data Analysis and Business Modeling

Author:   Wayne Winston
Publisher:   Microsoft Press,U.S.
Edition:   5th edition
ISBN:  

9781509304219


Pages:   864
Publication Date:   19 January 2017
Replaced By:   9781509305889
Format:   Paperback
Availability:   In Print   Availability explained
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Microsoft Excel Data Analysis and Business Modeling


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Overview

Students will master business modeling and analysis techniques with Microsoft Excel 2016, and transform data into bottom-line results. Written by award-winning educator Wayne Winston, this hands on, scenario-focused guide helps readers use Excel’s newest tools to ask the right questions and get accurate, actionable answers. This edition adds 150+ new problems with solutions, plus a chapter of basic spreadsheet models to make sure readers are fully up to speed.

Full Product Details

Author:   Wayne Winston
Publisher:   Microsoft Press,U.S.
Imprint:   Microsoft Press
Edition:   5th edition
Dimensions:   Width: 19.00cm , Height: 4.40cm , Length: 22.90cm
Weight:   1.437kg
ISBN:  

9781509304219


ISBN 10:   1509304215
Pages:   864
Publication Date:   19 January 2017
Audience:   Professional and scholarly ,  Professional & Vocational
Replaced By:   9781509305889
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

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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Author Information

WAYNE L. WINSTON is Professor Emeritus of Decision Sciences at Indiana University’s Kelley School of Business and Visiting Professor of Decision and Information Sciences at University of Houston Bauer College of Business. He has earned numerous MBA teaching awards. For more than 20 years, he has taught clients at Fortune 500 companies, various accounting groups, the US Navy, and the US Army how to use Excel to make smarter business decisions. Wayne and his business partner Jeff Sagarin developed the player-statistics tracking and rating system used by the Dallas Mavericks professional basketball team. He is also a two time  Jeopardy! champion.

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