# RTM’d today: Microsoft Excel 2010: Data Analysis and Business Modeling

We’re happy to announce that Microsoft Excel 2010: Data Analysis and Business Modeling, by Wayne L. Winston, shipped to the printer.  Award-winning MBA professor, statistician, and business consultant Wayne Winston shows you how to master the data analysis and modeling techniques used at leading companies to sharpen their competitive edge. This book will be available soon, but in the meantime here are the Table of Contents and an excerpt from the Introduction.

1 What’s New in Excel 2010

2 Range Names

3 Lookup Functions

4 The INDEX Function

5 The MATCH Function

6 Text Functions

7 Dates and Date Functions

8 Evaluating Investments by Using Net Present Value Criteria

9 Internal Rate of Return

10 More Excel Financial Functions

11 Circular References

12 IF Statements

13 Time and Time Functions

14 The Paste Special Command

15 Three-Dimensional Formulas

16 The Auditing Tool

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, and AVERAGEIFS Functions

22 The OFFSET Function

23 The INDIRECT Function

24 Conditional Formatting

25 Sorting in Excel

26 Tables

27 Spin Buttons, Scroll Bars, Option Buttons, Check Boxes, Combo Boxes, and Group List Boxes

28 An Introduction to Optimization with Excel Solver

29 Using Solver to Determine the Optimal Product Mix

30 Using Solver to Schedule Your Workforce

31 Using Solver to Solve Transportation or Distribution Problems

32 Using Solver for Capital Budgeting

33 Using Solver for Financial Planning

34 Using Solver to Rate Sports Teams

35 Warehouse Location and the GRG Multistart and Evolutionary Solver Engines

36 Penalties and the Evolutionary Solver

37 The Traveling Salesperson Problem

38 Importing Data from a Text File or Document

39 Importing Data from the Internet

40 Validating Data

41 Summarizing Data by Using Histograms

42 Summarizing Data by Using Descriptive Statistics

43 Using PivotTables and Slicers to Describe Data

44 Sparklines

45 Summarizing Data with Database Statistical Functions

46 Filtering Data and Removing Duplicates

47 Consolidating Data

48 Creating Subtotals

49 Estimating Straight Line Relationships

50 Modeling Exponential Growth

51 The Power Curve

52 Using Correlations to Summarize Relationships

53 Introduction to Multiple Regression

54 Incorporating Qualitative Factors into Multiple Regression

55 Modeling Nonlinearities and Interactions

56 Analysis of Variance: One-Way ANOVA

57 Randomized Blocks and Two-Way ANOVA

58 Using Moving Averages to Understand Time Series

59 Winters’s Method

60 Ratio-to-Moving-Average Forecast Method

61 Forecasting in the Presence of Special Events

62 An Introduction to Random Variables

63 The Binomial, Hypergeometric, and Negative Binomial Random Variables

64 The Poisson and Exponential Random Variable

65 The Normal Random Variable

66 Weibull and Beta Distributions: Modeling Machine Life and Duration of a Project

67 Making Probability Statements from Forecasts

68 Using the Lognormal Random Variable to Model Stock Prices

69 Introduction to Monte Carlo Simulation

70 Calculating an Optimal Bid

71 Simulating Stock Prices and Asset Allocation Modeling

72 Fun and Games: Simulating Gambling and Sporting Event Probabilities

73 Using Resampling to Analyze Data

74 Pricing Stock Options

75 Determining Customer Value

76 The Economic Order Quantity Inventory Model

77 Inventory Modeling with Uncertain Demand

78 Queuing Theory: The Mathematics of Waiting in Line

79 Estimating a Demand Curve

80 Pricing Products by Using Tie-Ins

81 Pricing Products by Using Subjectively Determined Demand

82 Nonlinear Pricing

83 Array Formulas and Functions

84 PowerPivot

# Introduction

Excerpt

Whether you work for a Fortune 500 corporation, a small company, a government agency, or a not-for-profit organization, if you’re reading this introduction the chances are you use Microsoft Excel in your daily work. Your job probably involves summarizing, reporting, and analyzing data. It might also involve building analytic models to help your employer increase profits, reduce costs, or manage operations more efficiently.

Since 1999, I’ve taught thousands of analysts at organizations such as 3M, Bristol-Myers
Squibb, Cisco Systems, Drugstore.com, eBay, Eli Lilly, Ford, General Electric, General Motors, Intel, Microsoft, NCR, Owens Corning, Pfizer, Proctor & Gamble, Tellabs, the U.S. Army, the U.S. Department of Defense, and Verizon how to use Excel more efficiently and productively in their jobs. Students have often told me that the tools and methods I teach in my classes have saved them hours of time each week and provided them with new and improved approaches for analyzing important business problems. Most of these classes used Excel 2003 or Excel 2007. With the added power of Excel 2010, you can be more productive than you ever dreamed! To paraphrase Alicia Silverstone in the movie Clueless, Excel 2007 is so five years ago.

I’ve used the techniques described in this book in my own consulting practice to solve many business problems. For example, I use Excel to help the Dallas Mavericks NBA basketball team evaluate referees, players, and lineups. During the last 15 years I have also taught Excel business modeling and data analysis classes to MBA students at Indiana University’s Kelley School of Business. (As proof of my teaching excellence, I have won BA teaching awards for 25 consecutive years, and have won the school’s overall MBA teaching award five times.) I would like to also note that 95 percent of MBA students at Indiana University take my spreadsheet modeling class even though it is an elective.

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