Statistics

Professors Norean Sharpe (Babson College), Dick De Veaux (Williams College), and Paul Velleman (Cornell University) have teamed up to provide an innovative new textbook for the undergraduate introductory business statistics course. These authors have taught at the finest business schools and draw on their consulting experience at leading companies to show students how statistical thinking is vital to modern decision making.

 

Managers make better business decisions when they understand statistics, and Business Statistics gives students the statistical tools and understanding to take them from the classroom to the boardroom. Hundreds of examples are based on current events and timely business topics. Short, accessible chapters allow for flexible coverage of important topics, while the conversational writing style maintains student interest and improves understanding.

 

Business Statistics includes Guided Examples that feature the authors’ signature Plan/Do/Report problem-solving method. Each worked example shows students how to clearly define the business decision to be made and plan which method to use, do the calculations and make the graphical displays, and finally report their findings, often in the form of a business memo. Every chapter reminds students of What Can Go Wrong and teaches them how to avoid making common statistical mistakes.

Volume I contains chapters 1–15 of the main text.

• Chapter Openers present a statistical issue in a managerial setting from a well-known company. These scenarios use real data in the context of business disciplines such as marketing, finance, or economics.
• Plan/Do/Report Guided Examples provide a model to help students approach and solve any business statistics problem. Reports are frequently presented in the form of a business memo, helping students become familiar with framing and communicating results in a business setting.
• A focus on checking assumptions and conditions emphasizes the need to verify assumptions when using statistical procedures. This focus is reiterated throughout the examples and exercises.
• Emphasis on graphing and exploring data. The consistent emphasis on the importance of displaying data is evident from the first chapters on understanding data right through to the complex model-building chapters at the end.
• The flexible topic coverage features short, modular chapters to accommodate any course objective or syllabus.
• Real data is used throughout the book in exercises, examples, and applications. Hundreds of motivating examples are based on current events and well-known companies. Students learn from the authors’ consulting experience and see how statistical thinking is vital to modern business decision making. This book follows the GAISE Guidelines, using real data and emphasizing real-world interpretations of analyses as often as possible.
• Math Boxes show the mathematical underpinnings—proofs, derivations, and justifications—of statistical methods and concepts. These boxes are set apart from the main narrative to avoid interrupting the explanation of the topic at hand.
• What Can Go Wrong? sections near the end of each chapter prepare students with the tools to detect common statistical errors and offer practice in debunking misuses of statistics.
• By Hand Boxes guide students on how to compute and arrive at solutions by hand, without the aid of technology. These optional discussions distill and explain formulas to help students through the calculation of a worked example.
• Just Checking questions within sections ask students to stop and think about what they’ve just read. Designed to check student understanding, these questions involve little calculation. Answers are provided at the end of the chapter so students can easily check their work.
• Ethics in Action vignettes in every chapter illustrate the judgment needed in statistical analysis. Students learn to identify ethically challenging issues and to propose ethically and statistically sound solutions. Questions are included for study and reflection.
• What Have We Learned? sections at the end of each chapter provide a summary and overview of important new concepts discussed, define new terms, and list the skills that students should have acquired from reading the chapter.
• Technology Help chapter sections often include annotated examples and offer guidance on using the most common statistics packages (Excel^®, MINITAB^®, JMP^®, Data Desk, and SPSS^®) to practice concepts in the chapters and get started with the technology of their choice.
• Mini Case Study Projects at the end of each chapter use real data and ask students to investigate a question or make a business decision. Students are asked to define the objective, plan the process, complete the analysis, and report their conclusion. Data for these projects are available on the included CD-ROM and the companion website, and are formatted for multiple software programs.
• Exercises within a set progress in difficulty and complexity. Generally, they start with a straightforward application of the chapter ideas. Next, they tackle larger problems but are broken into several parts to guide students through the logic of a complete analysis. Finally, students are asked to synthesize and incorporate their own ideas. Some of more challenging exercises would be ideal for group projects. Large data sets are provided on the accompanying CD-ROM and the companion website.

Volume I contains chapters 1—15 of the main text.

PART I: EXPLORING AND COLLECTING DATA

 

1. Statistics and Variation

 

2. Data

2.1 What Are Data?

2.2 Variable Types

2.3 Where, How, and When

 

3. Surveys and Sampling

3.1 Three Ideas of Sampling

3.2 A Census–Does it Make Sense?

3.3 Populations and Parameters

3.4 Simple Random Sample (SRS)

3.5 Other Sample Designs

3.6 Defining the Population

3.7 The Valid Survey

 

4. Displaying and Describing Categorical Data

4.1 The Three Rules of Data Analysis

4.2 Frequency Tables   

4.3 Charts

4.4 Contingency Tables

 

5. Randomness and Probability

5.1 Random Phenomena and Probability

5.2 The Non-existent Law of Averages

5.3 Different Types of Probability

5.4 Probability Rules

5.5 Joint Probability and Contingency Tables

5.6 Conditional Probability

5.7 Constructing Contingency Tables     

 

6. Displaying and Describing Quantitative Data

6.1 Displaying Distributions                              

6.2 Shape

6.3 Center

6.4 Spread of the Distribution   

6.5 Shape, Center, and Spread–A Summary     

6.6 Five-Number Summary and Boxplots

6.7 Comparing Groups

6.8 Identifying Outliers

6.9 Standardizing

6.10 Time Series Plots

*6.11 Transforming Skewed Data

 

PART II: UNDERSTANDING DATA AND DISTRIBUTIONS

 

7. Scatterplots, Association, and Correlation

7.1 Looking at Scatterplots

7.2 Assigning Roles to Variables in Scatterplots

7.3 Understanding Correlation

*7.4 Straightening Scatterplots

7.5 Lurking Variables and Causation      

 

8. Linear Regression

8.1 The Linear Model    

8.2 Correlation and the Line

8.3 Regression to the Mean

8.4 Checking the Model

8.5 Learning More from the Residuals                            

8.6 Variation in the Model and R2

8.7 Reality Check: Is the Regression Reasonable?

 

9. Sampling Distributions and the Normal Model

9.1 Modeling the Distribution of Sample Proportions     

9.2 Simulation  

9.3 The Normal Distribution

9.4 Practice with Normal Distribution Calculations

9.5 The Sampling Distribution for Proportions

9.6 Assumptions and Conditions

9.7 The Central Limit Theorem–The Fundamental Theorem of Statistics

9.8 The Sampling Distribution of the Mean

9.9 Sample Size–Diminishing Returns

9.10 How Sampling Distribution Models Work

 

10. Confidence Intervals for Proportions

10.1 A Confidence Interval

10.2 Margin of Error: Certainty vs. Precision      

10.3 Critical Values

10.4 Assumptions and Conditions

*10.5 A Confidence Interval for Small Samples

10.6 Choosing Sample Size

11. Testing Hypotheses about Proportions

11.1 Hypotheses

11.2 A Trial as a Hypothesis Test

11.3 P-values

11.4 The Reasoning of Hypothesis Testing                    

11.5 Alternative Hypotheses

11.6 Alpha Levels and Significance

11.7 Critical Values

11.8 Confidence Intervals and Hypothesis Tests

11.9 Two Types of Errors

*11.10 Power

 

12. Confidence Intervals and Hypothesis Tests for Means

12.1 The Sampling Distribution for the Mean

12.2 A Confidence Interval for Means

12.3 Assumptions and Conditions

12.4 Cautions About Interpreting Confidence Intervals

12.5 One-Sample t-Test

12.6 Sample Size         

12.7 Degrees of Freedom–Why (n-1)?

 

13. Comparing Two Means

13.1 Testing Differences Between Two Means

13.2 The Two-Sample t-test

13.3 Assumptions and Conditions

*13.4 A Confidence Interval for the Difference Between Two Means

13.5 The Pooled t-test

*13.6 Tukey’s Quick Test

 

14. Paired Samples and Blocks

14.1 Paired Data

14.2 Assumptions and Conditions

14.3 The Paired t-Test

14.4 How the Paired t-Test Works

 

15. Inference for Counts: Chi-Square Tests

15.1 Goodness of Fit Tests

15.2 Interpreting Chi-square Values

15.3 Examining the Residuals

15.4 The Chi-Square Test of Homogeneity

15.5 Comparing Two Proportions

15.6 Chi-Square Test of Independence

*Indicates an optional topic

Intro to Business Statistics - One or Two Term (Statistics)

 

Norean Sharpe (Ph.D. University of Virginia), as a researcher of statistical problems in business and a professor at a business school, understands the challenges and specific needs of the business student. She is currently Professor of Statistics at Babson College, where she is also Chair of the Division of Mathematics and Science. She is the recipient of the 2008 Women Who Make a Difference Award for female faculty at Babson. Prior to joining Babson, she taught statistics and applied mathematics courses for several years at Bowdoin College. Norean is coauthor of the recent text, A Casebook for Business Statistics: Laboratories for Decision Making, and has authored over 30 articles-primarily in the areas of statistics education and women in science. Norean currently serves as Associate Editor for CAUSE (Consortium for the Advancement of Undergraduate Statistics Education) and Associate Editor for the journal Cases in Business, Industry, and Government Statistics. Her research focuses on business forecasting and statistics education.

 

Richard D. De Veaux (Ph.D. Stanford University) is an internationally known educator, consultant, and lecturer. Dick has taught Statistics at a business school (The Wharton School of the University of Pennsylvania), an engineering school (Princeton University) and a liberal arts college (Williams College). He is an internationally known lecturer in data mining and is a consultant for many Fortune 500 companies in a wide variety of industries. While at Princeton, he won a Lifetime Award for Dedication and Excellence in Teaching. Since 1994, he has been a Professor of Statistics at Williams College. Dick holds degrees from Princeton University in Civil Engineering and Mathematics, and from Stanford University in Dance Education and Statistics, where he studied with Persi Diaconis. His research focuses on the analysis of large data sets and data mining in science and industry. Dick has won both the Wilcoxon and Shewell awards from the American Society for Quality and is a Fellow of the American Statistical Association. Dick is well known in industry, having consulted for such companies as American Express, Hewlett-Packard, Alcoa, DuPont, Pillsbury, General Electric, and Chemical Bank. He was named the “Statistician of the Year” for 2008 by the Boston Chapter of the American Statistical Association for his contributions to teaching, research, and consulting. In his spare time he is an avid cyclist and swimmer. He also is the founder and bass for the Doo-wop group, “Diminished Faculty,” and is a frequent soloist with various local choirs and orchestras. Dick is the father of four children.

 

Paul F. Velleman (Ph.D. Princeton University) has an international reputation for innovative statistics education. He designed the Data Desk® software package and is also the author and designer of the award-winning ActivStats® statistics package, for which he received the EDUCOM Medal for innovative uses of computers in teaching statistics and the ICTCM Award for Innovation in Using Technology in College Mathematics. He is the founder and CEO of Data Description, Inc. (www.datadesk.com), which supports both of these programs. He also developed the Internet site, Data and Story Library (DASL) (dasl.datadesk.com), which provides data sets for teaching Statistics. Paul co-authored (with David Hoaglin) the book ABCs of Exploratory Data Analysis. Paul has taught Statistics at Cornell University on the faculty of the School of Industrial and Labor Relations since 1975. His research often focuses on statistical graphics and data analysis methods. Paul is a Fellow of the American Statistical Association and of the American Association for the Advancement of Science. Paul’s experience as a professor, entrepreneur and business leader brings a unique perspective to the book.

 

Dick De Veaux and Paul Velleman have authored successful books in the introductory college and AP High School market with Dave Bock, including Intro Stats, Third Edition (Pearson, 2009), Stats: Modeling the World, Third Edition (Pearson, 2010), and Stats: Data and Models, Second Edition (Pearson, 2008).

View a Sample Chapter PDF:

  

• Interwrite Personal Response System
  EduCue, Addison-Wesley & Benjamin Cummings
  © 2004 | Benjamin Cummings | Electronic Supplement | Instock
  ISBN-10: 0321267354 | ISBN-13: 9780321267351
  
  
  
• iClicker Classroom Response System
  iClicker, Addison-Wesley & Benjamin Cummings
  © 2008 | Benjamin Cummings | Electronic Supplement | Instock
  ISBN-10: 032153705X | ISBN-13: 9780321537058
  
  
  

Pearson Higher Education offers special pricing when you choose to package your text with other student resources. If you're interested in creating a cost-saving package for your students, contact your Pearson Higher Education representative for pricing and ordering information.

Pearson Higher Education offers special pricing when you choose to package your text with other student resources. If you're interested in creating a cost-saving package for your students contact your Pearson Higher Education representative.