Cover
About the Authors
Brief Contents
Contents
Preface
Chapter 1: Introduction to Business Analytics
1-1 Introduction
1-2 Overview of the Book
1-3 Introduction to Spreadsheet Modeling
1-4 Conclusion
Summary of Key Terms
Problems
Part 1: Data Analysis
Chapter 2: Describing the Distribution of a Variable
2-1 Introduction
2-2 Basic Concepts
2-3 Summarizing Categorical Variables
2-4 Summarizing Numeric Variables
2-5 Time Series Data
2-6 Outliers and Missing Values
2-7 Excel Tables for Filtering, Sorting, and Summarizing
2-8 Conclusion
Summary of Key Terms
Problems
Case 2.1 Correct Interpretation of Means
Case 2.2 The Dow Jones Industrial Average
Case 2.3 Home and Condo Prices
Appendix: Introduction to StatTools
Chapter 3: Finding Relationships among Variables
3-1 Introduction
3-2 Relationships among Categorical Variables
3-3 Relationships among Categorical Variables and a Numeric Variable
3-4 Relationships among Numeric Variables
3-5 Pivot Tables
3-6 Conclusion
Summary of Key Terms
Problems
Case 3.1 Customer Arrivals at Bank98
Case 3.2 Saving, Spending, and Social Climbing
Case 3.3 Churn in the Cellular Phone Market
Case 3.4 Southwest Border Apprehensions and Unemployment
Appendix: Using StatTools to Find Relationships
Chapter 4: Business Intelligence (BI) Tools for Data Analysis
4-1 Introduction
4-2 Importing Data into Excel with Power Query
4-3 Data Analysis with Power Pivot
4-4 Data Visualization with Tableau Public
4-5 Data Cleansing
4-6 Conclusion
Summary of Key Terms
Problems
Part 2: Probability and Decision Making under Uncertainty
Chapter 5: Probability and Probability Distributions
5-1 Introduction
5-2 Probability Essentials
5-3 Probability Distribution of a Random Variable
5-4 The Normal Distribution
5-5 The Binomial Distribution
5-6 The Poisson and Exponential Distributions
5-7 Conclusion
Summary of Key Terms
Problems
Case 5.1 Simpson's Paradox
Case 5.2 EuroWatch Company
Case 5.3 Cashing in on the Lottery
Chapter 6: Decision Making under Uncertainty
6-1 Introduction
6-2 Elements of Decision Analysis
6-3 EMV and Decision Trees
6-4 One-Stage Decision Problems
6-5 The PrecisionTree Add-In
6-6 Multistage Decision Problems
6-7 The Role of Risk Aversion
6-8 Conclusion
Summary of Key Terms
Problems
Case 6.1 Jogger Shoe Company
Case 6.2 Westhouser Paper Company
Case 6.3 Electronic Timing System for Olympics
Case 6.4 Developing a Helicopter Component for the Army
Appendix: Decision Trees with DADM_Tools
Part 3: Statistical Inference
Chapter 7: Sampling and Sampling Distributions
7-1 Introduction
7-2 Sampling Terminology
7-3 Methods for Selecting Random Samples
7-4 Introduction to Estimation
7-5 Conclusion
Summary of Key Terms
Problems
Chapter 8: Confidence Interval Estimation
8-1 Introduction
8-2 Sampling Distributions
8-3 Confidence Interval for a Mean
8-4 Confidence Interval for a Total
8-5 Confidence Interval for a Proportion
8-6 Confidence Interval for a Standard Deviation
8-7 Confidence Interval for the Difference between Means
8-8 Confidence Interval for the Difference between Proportions
8-9 Sample Size Selection
8-10 Conclusion
Summary of Key Terms
Problems
Case 8.1 Harrigan University Admissions
Case 8.2 Employee Retention at D&Y
Case 8.3 Delivery Times at SnowPea Restaurant
Chapter 9: Hypothesis Testing
9-1 Introduction
9-2 Concepts in Hypothesis Testing
9-3 Hypothesis Tests for a Population Mean
9-4 Hypothesis Tests for Other Parameters
9-5 Tests for Normality
9-6 Chi-Square Test for Independence
9-7 Conclusion
Summary of Key Terms
Problems
Case 9.1 Regression toward the Mean
Case 9.2 Friday Effect in the Stock Market
Case 9.3 Removing Vioxx from the Market
Part 4: Regression Analysis and Time Series Forecasting
Chapter 10: Regression Analysis: Estimating Relationships
10-1 Introduction
10-2 Scatterplots: Graphing Relationships
10-3 Correlations: Indicators of Linear Relationships
10-4 Simple Linear Regression
10-5 Multiple Regression
10-6 Modeling Possibilities
10-7 Validation of the Fit
10-8 Conclusion
Summary of Key Terms
Problems
Case 10.1 Quantity Discounts at Firm Chair Company
Case 10.2 Housing Price Structure in Mid City
Case 10.3 Demand for French Bread at Howie's Bakery
Case 10.4 Investing for Retirement
Chapter 11: Regression Analysis: Statistical Inference
11-1 Introduction
11-2 The Statistical Model
11-3 Inferences about the Regression Coefficients
11-4 Multicollinearity
11-5 Include/Exclude Decisions
11-6 Stepwise Regression
11-7 Outliers
11-8 Violations of Regression Assumptions
11-9 Prediction
11-10 Conclusion
Summary of Key Terms
Problems
Case 11.1 Heating Oil at Dupree Fuels
Case 11.2 Developing a Flexible Budget at the Gunderson Plant
Case 11.3 Forecasting Overhead at Wagner Printers
Chapter 12: Time Series Analysis and Forecasting
12-1 Introduction
12-2 Forecasting Methods: An Overview
12-3 Testing for Randomness
12-4 Regression-Based Trend Models
12-5 The Random Walk Model
12-6 Moving Averages Forecasts
12-7 Exponential Smoothing Forecasts
12-8 Seasonal Models
12-9 Conclusion
Summary of Key Terms
Problems
Case 12.1 Arrivals at the Credit Union
Case 12.2 Forecasting Weekly Sales at Amanta
Appendix: Alternative Forecasting Software
Part 5: Optimization and Simulation Modeling
Chapter 13: Introduction to Optimization Modeling
13-1 Introduction
13-2 Introduction to Optimization
13-3 A Two-Variable Product Mix Model
13-4 Sensitivity Analysis
13-5 Properties of Linear Models
13-6 Infeasibility and Unboundedness
13-7 A Larger Product Mix Model
13-8 A Multiperiod Production Model
13-9 A Comparison of Algebraic and Spreadsheet Models
13-10 A Decision Support System
13-11 Conclusion
Summary of Key Terms
Problems
Case 13.1 Shelby Shelving
Chapter 14: Optimization Models
14-1 Introduction
14-2 Employee Scheduling Models
14-3 Blending Models
14-4 Logistics Models
14-5 Aggregate Planning Models
14-6 Financial Models
14-7 Integer Optimization Models
14-8 Nonlinear Optimization Models
14-9 Conclusion
Summary of Key Terms
Problems
Case 14.1 Giant Motor Company
Case 14.2 GMS Stock Hedging
Chapter 15: Introduction to Simulation Modeling
15-1 Introduction
15-2 Probability Distributions for Input Variables
15-3 Simulation and the Flaw of Averages
15-4 Simulation with Built-in Excel Tools
15-5 Simulation with @RISK
15-6 The Effects of Input Distributions on Results
15-7 Conclusion
Summary of Key Terms
Problems
Case 15.1 Ski Jacket Production
Case 15.2 Ebony Bath Soap
Appendix: Simulation with DADM_Tools
Chapter 16: Simulation Models
16-1 Introduction
16-2 Operations Models
16-3 Financial Models
16-4 Marketing Models
16-5 Simulating Games of Chance
16-6 Conclusion
Summary of Key Terms
Problems
Case 16.1 College Fund Investment
Case 16.2 Bond Investment Strategy
Part 6: Advanced Data Analysis
Chapter 17: Data Mining
17-1 Introduction
17-2 Classification Methods
17-3 Clustering Methods
17-4 Conclusion
Summary of Key Terms
Problems
Case 17.1 Houston Area Survey
References
Index