Nelson Higher Education

Higher Education

Data Analysis and Decision Making, 4th Edition

  • Includes Online Content Printed Access Card.
  • S. Christian Albright
  • Wayne Winston
  • Christopher Zappe
  • ISBN-10: 0538476125
  • ISBN-13: 9780538476126
  • 1080 Pages | Hardcover
  • Previous Editions: 2009, 2006, 2003
  • COPYRIGHT: 2011 Published
Request a Copy for Review

Overview

About the Product

DATA ANALYSIS AND DECISION MAKING emphasizes data analysis, modeling, and spreadsheet use in statistics and management science. Professional Excel software add-ins are included, making this text a market leader in its first edition for its clarity of writing, a teach-by-example approach, and complete Excel integration. This edition is compatible with Excel 2007 and the corresponding add-ins for Excel 2007. Updates regarding Excel 2010 are included where applicable.

Features

  • All updated screenshots and accompanying explanations to reflect Excel 2007 and updated add-ins. Tips on Excel 2010 have been added where applicable. This edition now provides access to Excel add-in software via an access code to a Premium Online Content Website for every student purchasing a new book.

  • IRCD: PowerPoints, and Solutions, Case, and Example files have been updated to reflect the core text 4th edition. The Test Bank has been updated with new questions and is now offered in ExamView testing software.

About the Author

S. Christian Albright

S. Christian Albright received both his B.S. degree in mathematics and his Ph.D. in operations research from Stanford. He then taught in the Operations and Decision Technologies Department in the Kelley School of Business at Indiana University until his retirement in 2011. He taught courses in management science, computer simulation and statistics to all levels of business students, including undergraduate, M.B.A. and Ph.D. students. He has published more than 20 articles in leading operations research journals in applied probability. After retiring, he worked for several years for the Palisade software company. Now living in Hilton Head, SC, he continues to revise several successful textbooks, including this edition, PRACTICAL MANAGEMENT SCIENCE and VBA FOR MODELERS.

Wayne Winston

Wayne L. Winston is Professor of Operations and Decision Technologies in the Kelley School of Business at Indiana University, where he has taught since 1975. Wayne received his B.S. degree in Mathematics from MIT and his Ph.D. degree in Operations Research from Yale. He has written the successful textbooks OPERATIONS RESEARCH: APPLICATIONS AND ALGORITHMS, MATHEMATICAL PROGRAMMING: APPLICATIONS AND ALGORITHMS, SIMULATION MODELING WITH @RISK, PRATICAL MANAGEMENT SCIENCE, DATA ANALYSIS FOR MANAGERS, SPREADSHEET MODELING AND APPLICATIONS, AND FINANCIAL MODELS USING SIMULATION AND OPTIMIZATION. Wayne has published over 20 articles in leading journals and has won many teaching awards, including the school-wide MBA award four times. His current interest is in showing how spreadsheet models can be used to solve business problems in all disciplines, particularly in finance and marketing.

Christopher Zappe

Christopher J. Zappe earned his B.A. in Mathematics from DePauw University in 1983 and his M.B.A. and Ph.D. in Decision Sciences from Indiana University in 1987 and 1988, respectively. Since 1993, Professor Zappe has been serving as an associate professor in the decision sciences area of the Department of Management at Bucknell University (Lewisburg, PA). He has published articles in scholarly journals such as Managerial and Decision Economics, OMEGA, Naval Research Logistics, and Interfaces.

Table of Contents

Preface
1. Introduction to Data Analysis and Decision Making.
1.1. Introduction.
1.2. An Overview of the Book.
1.3. Modeling and Models.
1.4. Conclusion.
PART I: EXPLORING DATA.
2. Describing the Distribution of a Single Variable.
2.1 Introduction.
2.2 Basic Concepts.
2.3 Descriptive Measures for Categorical Variables.
2.4 Descriptive Measures for Numerical Variables.
2.5 Time Series Data.
2.6 Outliers and Missing Values.
2.7 Excel Tables for Filtering, Sorting, and Summarizing.
2.8 Conclusion.
3. Finding Relationships Among Variables.
3.1 Introduction.
3.2 Relationships Among Categorical Variables.
3.3 Relationships Among Categorical Variables and a Numerical Variable.
3.4 Relationships Among Numerical Variables.
3.5 Pivot Tables.
3.6 An Extended Example.
3.7 Conclusion.
PART II: PROBABILITY AND DECISION MAKING UNDER UNCERTAINTY
4. Probability and Probability Distributions.
4.1. Introduction.
4.2. Probability Essentials.
4.3. Distribution of a Single Random Variable.
4.4. An Introduction to Simulation.
4.5. Distribution of Two Random Variables: Scenario Approach.
4.6. Distribution of Two Random Variables: Joint Probability Approach.
4.7. Independent Random Variables.
4.8. Weighted Sums of Random Variables.
4.9. Conclusion.
5. Normal, Binomial, Poisson, and Exponential Distributions.
5.1. Introduction.
5.2. The Normal Distribution.
5.3. Applications of the Normal Distribution.
5.4. The Binomial Distribution.
5.5. Applications of the Binomial Distribution.
5.6. The Poisson and Exponential Distributions.
5.7. Fitting a Probability Distribution to Data with @RISK.
5.8. Conclusion.
6. Decision Making Under Uncertainty.
6.1. Introduction.
6.2. Elements of a Decision Analysis.
6.3. The PrecisionTree Add-In.
6.4. Bayes’ Rule.
6.5. Multistage Decision Problems.
6.6. Incorporating Attitudes Toward Risk.
6.7. Conclusion.
PART III: STATISTICAL INFERENCE.
7. Sampling and Sampling Distributions.
7.1. Introduction.
7.2. Sampling Terminology.
7.3. Methods for Selecting Random Samples.
7.4. An Introduction to Estimation.
7.5. Conclusion.
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. Controlling Confidence Interval Length.
8.10. Conclusion.
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. One-Way ANOVA.
9.8. Conclusion.
PART IV: REGRESSION ANALYSIS AND TIME SERIES FORECASTING.
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.
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. The Partial F Test.
11.8. Outliers.
11.9. Violations of Regression Assumptions.
11.10. Prediction.
11.11. Conclusion.
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. Autoregression Models.
12.7. Moving Averages.
12.8. Exponential Smoothing.
12.9. Seasonal Models.
12.10. Conclusion.
PART V: OPTIMIZATION AND SIMULATION MODELING.
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.
14. Optimization Models.
14.1. Introduction.
14.2. Worker Scheduling Models.
14.3. Blending Models.
14.4. Logistics Models.
14.5. Aggregate Planning Models.
14.6. Financial Models.
14.7. Integer Programming Models.
14.8. Nonlinear Programming Models.
14.9. Conclusion.
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. Introduction to the @RISK Add-in.
15.6. The Effects of Input Distributions on Results.
15.7. Conclusion.
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. An Automated Template for @RISK Models.
16.7. Conclusion.
PART VI: BONUS ONLINE MATERIAL
2 Using the Advanced Filter and Database Functions.
17. Importing Data into Excel.
17.1 Introduction.
17.2 Rearranging Excel Data.
17.3 Importing Text Data.
17.4 Importing Relational Database Data.
17.5 Web Queries.
17.6 Cleansing the Data.
17.7 Conclusion.

New to this edition

  • Chapters 2 and 3 are completely rewritten and reorganized, focusing on the description of one variable at a time, and relationships between variables. Both chapters have more coverage of categorical variables, as well as new and more interesting data sets in the examples. Many of the problems in previous editions were deleted or updated, and a number of brand new problems were added for relevance to current statistical analysis. A problem guide is available to instructors showing the context of each of the "data" problems, and it also shows the correspondence between problems in this edition and problems in the previous edition.
  • The previous edition's Chapter 4 is renamed as Chapter 17, Importing Data into Excel, and is completely rewritten with its section on Excel tables located in Chapter 2. (Previous edition chapters 5–17 were renumbered 4–16.)
  • The book is still based on Excel 2007, but notes about changes in Excel 2010 have been added where it applies. Specifically, there is a small section on the new slicers for pivot tables, and there are several mentions of the new statistical functions (although the old functions still work).
  • Each chapter now has 10-20 more consistent and relevant "Conceptual Questions" in the end-of-chapter sections.
  • The first two LP examples in Chapter 13 (replacing the former Chapter 14) are replaced by two product mix models, where the second builds on the first. The previous “diet” model was overly complex as a first LP example.
  • Several chapter-opening vignettes are replaced with newer and more interesting ones and there are now many short "fundamental insights" throughout the chapters. These insights are designed to allow the students to step back from the details and see the really important ideas.

Supplements

All supplements have been updated in coordination with the Main title.
Please see Main title page for new to this edition information.

Instructor Supplements

Business Statistics CourseMate with eBook Instant Access Code  (ISBN-10: 1111747830 | ISBN-13: 9781111747831)

Interested in a simple way to complement your text and course content with study and practice materials? Cengage Learning’s Decision Sciences CourseMate brings course concepts to life with interactive learning, study, and exam preparation tools that support the printed textbook. Watch student comprehension soar as your class works with the printed textbook and the textbook-specific website. Decision Sciences CourseMate goes beyond the book to deliver what you need! The Student Solutions Files for Albright/Winston/Zappe’s Data Analysis and Decision Making, 4e, are now included with CourseMate.

Student Solutions Manual Instant Access Code  (ISBN-10: 1111529051 | ISBN-13: 9781111529055)

The Student Solutions Manual contains the worked solutions to most of the odd-numbered problems found in the text. Problems indicated by a blue box in the textbook have a corresponding answer in the Student Solutions Manual. The Student Solutions Manual is available for purchase on CengageBrain.com. (Instructors have acces to ALL solutions on the IRCD and instructor companion website.)

Instructor's Resource CD-ROM  (ISBN-10: 1111529469 | ISBN-13: 9781111529468)

The IRCD includes Solutions, Case and Example files, PowerPoints, and Test Bank in ExamView. Solutions, case, and example files are updated to reflect new sections of the 4th edition. A full set of comprehensive PowerPoints are provided to aid class instruction. The presentation focuses on the book examples and has been updated to reflect the 4th edition text material. The Test Bank is updated with new questions to reflect the 4th edition updates and is now offered in ExamView testing software.

Online Content Instant Access Code  (ISBN-10: 1111575282 | ISBN-13: 9781111575281)

Student Supplements

Business Statistics CourseMate with eBook Instant Access Code  (ISBN-10: 1111747830 | ISBN-13: 9781111747831)

The more you study, the better the results. Make the most of your study time by accessing everything you need to succeed in one place. Read your textbook, take notes, review flashcards, and take practice quizzes—online with CourseMate. The Student Solutions Files for Albright/Winston/Zappe’s Data Analysis and Decision Making, 4e, are now included with CourseMate.

Student Solutions Manual Instant Access Code  (ISBN-10: 1111529051 | ISBN-13: 9781111529055)

The Student Solutions Manual contains the worked solutions to most of the odd-numbered problems found in the text. Problems indicated by a blue box in the textbook have a corresponding answer in the Student Solutions Manual. The Student Solutions Manual is available for purchase on CengageBrain.com.

Online Content Instant Access Code  (ISBN-10: 1111575282 | ISBN-13: 9781111575281)