Microsoft Office Excel 2007: Data Analysis and Business Modeling

Microsoft Office Excel 2007: Data Analysis and Business Modeling

by Wayne Winston

Paperback(Second Edition)

$39.99

Product Details

ISBN-13: 9780735623965
Publisher: Microsoft Press
Publication date: 05/30/2007
Series: Business Skills Series
Edition description: Second Edition
Pages: 624
Product dimensions: 7.38(w) x 9.00(h) x 1.44(d)

About the Author

Wayne L. Winston is a professor of Decision Sciences at Indiana University's Kelley School of Business and has earned numerous MBA teaching awards. For 20+ years, he has taught clients at Fortune 500 companies 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.

Table of Contents

Preface;
What You Should Know Before Reading this Book;
How to Use this Book;
Using the Companion CD;
Support Information;
Acknowledgments;
Introduction to Excel 2007: What’s New?;
Chapter 1: Range Names;
1.1 How Can I Create Named Ranges?;
1.2 Remarks;
1.3 Problems;
Chapter 2: Lookup Functions;
2.1 Syntax of the Lookup Functions;
2.2 Problems;
Chapter 3: The INDEX Function;
3.1 Syntax of the INDEX Function;
3.2 Problems;
Chapter 4: The MATCH Function;
4.1 Problems;
Chapter 5: Text Functions;
5.1 Text Function Syntax;
5.2 Text Functions in Action;
5.3 Extracting Data by Using the Text To Columns Wizard;
5.4 Problems;
Chapter 6: Dates and Date Functions;
6.1 Problems;
Chapter 7: Evaluating Investments by Using Net Present Value Criteria;
7.1 Problems;
Chapter 8: Internal Rate of Return;
8.1 Problems;
Chapter 9: More Excel Financial Functions;
9.1 CUMPRINC and CUMIPMT Functions;
9.2 Problems;
Chapter 10: Circular References;
10.1 Problems;
Chapter 11: IF Statements;
11.1 Problems;
Chapter 12: Time and Time Functions;
12.1 Problems;
Chapter 13: The Paste Special Command;
13.1 Problems;
Chapter 14: The Auditing Tool;
14.1 Problems;
Chapter 15: Sensitivity Analysis with Data Tables;
15.1 Problems;
Chapter 16: The Goal Seek Command;
16.1 Problems;
Chapter 17: Using the Scenario Manager for Sensitivity Analysis;
17.1 Remarks;
17.2 Problems;
Chapter 18: The COUNTIF, COUNTIFS, COUNT, COUNTA, and COUNTBLANK Functions;
18.1 Remarks;
18.2 Problems;
Chapter 19: The SUMIF, AVERAGEIF, SUMIFS, and AVERAGEIFS Functions;
19.1 Problems;
Chapter 20: The OFFSET Function;
20.1 Remark;
20.2 Problems;
Chapter 21: The INDIRECT Function;
21.1 Problems;
Chapter 22: Conditional Formatting;
22.1 Problems;
Chapter 23: Sorting in Excel;
23.1 Problems;
Chapter 24: Tables;
24.1 Problems;
Chapter 25: Spin Buttons, Scroll Bars, Option Buttons, Check Boxes, Combo Boxes, and Group List Boxes;
25.1 Spin Buttons and Scroll Bars;
25.2 Problems;
Chapter 26: An Introduction to Optimization with Excel Solver;
26.1 Problems;
Chapter 27: Using Solver to Determine the Optimal Product Mix;
27.1 Problems;
Chapter 28: Using Solver to Schedule Your Workforce;
28.1 Problems;
Chapter 29: Using Solver to Solve Transportation or Distribution Problems;
29.1 Problems;
Chapter 30: Using Solver for Capital Budgeting;
30.1 Handling Other Constraints;
30.2 Problems;
Chapter 31: Using Solver for Financial Planning;
31.1 Problems;
Chapter 32: Using Solver to Rate Sports Teams;
32.1 Problems;
Chapter 33: Importing Data from a Text File or Document;
33.1 Problems;
Chapter 34: Importing Data from the Internet;
34.1 Problems;
Chapter 35: Validating Data;
35.1 Remarks;
35.2 Problems;
Chapter 36: Summarizing Data by Using Histograms;
36.1 Problems;
Chapter 37: Summarizing Data by Using Descriptive Statistics;
37.1 Mean;
37.2 Median;
37.3 Mode;
37.4 Kurtosis;
37.5 Sample variance and sample standard deviation;
37.6 Range;
37.7 Problems;
Chapter 38: Using PivotTables to Describe Data;
38.1 Remarks About Grouping;
38.2 Problems;
Chapter 39: Summarizing Data with Database Statistical Functions;
39.1 Problems;
Chapter 40: Filtering Data and Removing Duplicates;
40.1 Problems;
Chapter 41: Consolidating Data;
41.1 Problems;
Chapter 42: Creating Subtotals;
42.1 Problems;
Chapter 43: Estimating Straight Line Relationships;
43.1 Problems;
Chapter 44: Modeling Exponential Growth;
44.1 Problems;
Chapter 45: The Power Curve;
45.1 Problems;
Chapter 46: Using Correlations to Summarize Relationships;
46.1 Filling in the correlation matrix;
46.2 Using the CORREL function;
46.3 Relationship between correlation and R2;
46.4 Correlation and regression towards the mean;
46.5 Problems;
Chapter 47: Introduction to Multiple Regression;
47.1 What is the best prediction equation?;
Chapter 48: Incorporating Qualitative Factors into Multiple Regression;
Chapter 49: Modeling Nonlinearities and Interactions;
49.1 Problems for Chapters 47 Through 49;
Chapter 50: Analysis of Variance: One-Way ANOVA;
50.1 Problems;
Chapter 51: Randomized Blocks and Two-Way ANOVA;
51.1 Problems;
Chapter 52: Using Moving Averages to Understand Time Series;
52.1 Problem;
Chapter 53: Winter’s Method;
53.1 Time Series Characteristics;
53.2 Parameter Definitions;
53.3 Initializing Winter’s Method;
53.4 Estimating the Smoothing Constants;
53.5 Remarks;
53.6 Problems;
Chapter 54: Forecasting in the Presence of Special Events;
54.1 Problems;
Chapter 55: An Introduction to Random Variables;
55.1 Problems;
Chapter 56: The Binomial, Hypergeometric, and Negative Binomial Random Variables;
56.1 Coke or Pepsi;
56.2 Elevator Rails;
56.3 Airline Overbooking;
56.4 Problems;
Chapter 57: The Poisson and Exponential Random Variable;
57.1 Problems;
Chapter 58: The Normal Random Variable;
58.1 What fraction of people have an IQ of less than 90?;
58.2 What fraction of all people have IQs from 95 through 120?;
58.3 What fraction of all people have IQs of at least 130?;
58.4 Problems;
Chapter 59: Weibull and Beta Distributions: Modeling Machine Life and Duration of a Project;
59.1 What is the probability that a machine will last at least 20 hours?;
59.2 What is the probability that a machine will last from 15 through 30 hours?;
59.3 Problems;
Chapter 60: Introduction to Monte Carlo Simulation;
60.1 Problems;
Chapter 61: Calculating an Optimal Bid;
61.1 Problems;
Chapter 62: Simulating Stock Prices and Asset Allocation Modeling;
62.1 Problems;
Chapter 63: Fun and Games: Simulating Gambling and Sporting Event Probabilities;
63.1 Problems;
Chapter 64: Using Resampling to Analyze Data;
64.1 Problems;
Chapter 65: Pricing Stock Options;
65.1 Problems;
Chapter 66: Determining Customer Value;
66.1 Problems;
Chapter 67: The Economic Order Quantity Inventory Model;
67.1 Problems;
Chapter 68: Inventory Modeling with Uncertain Demand;
68.1 The back-order case;
68.2 The lost-sales case;
68.3 Problems;
Chapter 69: Queuing Theory: The Mathematics of Waiting in Line;
69.1 Problems;
Chapter 70: Estimating a Demand Curve;
70.1 Problems;
Chapter 71: Pricing Products by Using Tie-Ins;
71.1 Problems;
Chapter 72: Pricing Products by Using Subjectively Determined Demand;
72.1 Problems;
Chapter 73: Nonlinear Pricing;
73.1 Problems;
Chapter 74: Array Formulas and Functions;
74.1 How many units of makeup did Jen sell?;
74.2 How many units of lipstick did Jen sell?;
74.3 How many units were sold by Jen or were lipstick?;
74.4 Can I summarize the number of units of each product sold by each salesperson?;
74.5 Problems;
About the Author;

Customer Reviews

Most Helpful Customer Reviews

See All Customer Reviews