Microsoft Excel 2019 Data Analysis and Business Modeling

by Wayne Winston

Overview

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

Product Details

ISBN-13:	9781509306084
Publisher:	Pearson Education
Publication date:	03/28/2019
Series:	Business Skills
Sold by:	Barnes & Noble
Format:	eBook
Pages:	864
Sales rank:	169,262
File size:	81 MB
Note:	This product may take a few minutes to download.
Age Range:	18 Years

About the Author

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

• 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 
• Chapter 20The 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
• C