Statistics for Business: Decision Making and Analysis

Robert A. Stine / Dean Foster  
Total pages
August 2013
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Statistics for Business: Decision Making and Analysis


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In Statistics for Business: Decision Making and Analysis, authors Robert Stine and Dean Foster of the University of Pennsylvania’s Wharton School, take a sophisticated approach to teaching statistics in the context of making good business decisions. The authors show students how to recognize and understand each business question, use statistical tools to do the analysis, and how to communicate their results clearly and concisely.


In addition to providing cases and real data to demonstrate real business situations, this text provides resources to support understanding and engagement. A successful problem-solving framework in the 4-M Examples (Motivation, Method, Mechanics, Message) model a clear outline for solving problems, new What Do You Think questions give students an opportunity to stop and check their understanding as they read, and new learning objectives guide students through each chapter and help them to review major goals. Software Hints provide instructions for using the most up-to-date technology packages. The Second Edition also includes expanded coverage and instruction of Excel® 2010 and the XLSTAT add-in.


The MyStatLab course management system includes increased exercise coverage with the Second Edition, along with 100% of the You Do It exercises and a library of 1,000 Conceptual Questions that require students to apply their statistical understanding to conceptual business scenarios. Business Insight Videos show students how statistical methods are used by real businesses, and new StatTalk Videos present statistical concepts through a series of fun, brief, real-world examples. Technology tutorial videos at the exercise level support software use.


Statistics in Practice: Preparing Students for Real Business

  • 4-M Examples (Motivation, Method, Mechanics, Message) provide a consistent methodology used for worked-out examples. This approach gives students a consistent structure for solving problems and presenting their findings in the appropriate context.
  • Running Business Examples start each chapter by framing a business question to motivate the contents of the chapter. The example is referenced throughout the chapter when new statistical methods are presented.
  • Statistics in Action case studies follow each of the four parts of the book. These longer applications expand on the statistical methods presented within the preceding part and use them to delve into substantive aspects of real-world business cases.
  • Video resources available in MyStatLab offer students insight into how statistical concepts are applied in the business world and the world around us.
    • Business Insight Videos show how statistical methods are used by real businesses.
    • NEW! StatTalk Videos present statistical concepts through a series of fun, brief, real-world vignettes.

Practice & Support: Challenging Students to Assess, Analyze and Report

  • NEW! More than 150 exercises are new or have been updated to provide readers with the most up-to-date and relevant data available.
  • Exercises are divided into five types. Each type focuses on a particular skill to build a deeper understanding of business statistics.
    • Mix and Match and True/False problems test whether students recognize symbols and important steps of calculations.
    • Think About It questions encourage students to pull together concepts and ideas from the chapter; no technology is required.
    • You Do It problems provide practice working through the mechanics of solving a problem (statistical software usage is recommended). These exercises apply the statistical concepts students have learned in the chapter to data related to a business application. Data are available on the included CD-ROM.
    • 4-M Questions are richer, more substantive problems that mimic real applications of statistics in business. Data are available on the included CD-ROM.
  • Support
    • NEW! 30 new What Do You Think? questions check students’ comprehension of the important ideas in the preceding section, ensuring that they understand the concepts before moving on in the chapter.
    • Caution icons indicate a concept that can be troublesome and helps students avoid making common mistakes.
    • Tip icons highlight important ideas or hints within the exposition so that readers don’t overlook them.
    • Best Practices and Pitfalls listed at the end of every chapter offer reminders to help students avoid mistakes such as using the wrong method for a situation, or misinterpreting results.

Technology Integration: Giving Students More Tools for Their Future Careers

  • Software Hints at the end of each chapter provide relevant commands for popular statistics packages: Excel®, Minitab®, and JMP®.
  • Extensive graphics, including Excel screenshots throughout the chapters and exercise sets, give students the opportunity to get familiar with seeing and interpreting statistical software output.
  • Technology Tutorial Videos and Study Cards within MyStatLab provide targeted guidance to using statistical software. (Study Cards are available for bundling.)


New to this Edition

Many features and resources have been updated to better support understanding and engagement, in addition to providing cases and real data to demonstrate real business situations.

  • Additional Excel® screenshots throughout the exercise sets offer students practice interpreting statistical software output.
  • 30 new What Do You Think? questions check students’ comprehension of the important ideas in the preceding section, ensuring that they understand the concepts before moving on in the chapter.
  • Each chapter now includes a list of learning objectives that provide guidance as students explore each chapter and review the major goals of the chapter.
  • More than 150 exercises are new or have been updated to provide readers with the most up-to-date and relevant data available.
  • This edition expands coverage of chi-squared tests to a full chapter (Chapter 18).
  • Online supplementary material includes methods to use when standard procedures fail (Chapter 17 of the previous edition) and further coverage of two-way analysis of variance and the practice of building regression models.


Table of Contents


Index of Application




1. Introduction

1.1 What Is Statistics?

1.2 Previews


2. Data

2.1 Data Tables

2.2 Categorical and Numerical Data

2.3 Recoding and Aggregation

2.4 Time Series

2.5 Further Attributes of Data

   Chapter Summary


3. Describing Categorical Data

3.1 Looking at Data

3.2 Charts of Categorical Data

3.3 The Area Principle

3.4 Mode and Median

   Chapter Summary


4. Describing Numerical Data

4.1 Summaries of Numerical Variables

4.2 Histograms

4.3 Boxplot

4.4 Shape of a Distribution

4.5 Epilog

   Chapter Summary


5. Association between Categorical Variables

5.1 Contingency Tables

5.2 Lurking Variables and Simpson's Paradox

5.3 Strength of Association

   Chapter Summary


6. Association between Quantitative Variables

6.1 Scatterplots

6.2 Association in Scatterplots

6.3 Measuring Association

6.4 Summarizing Association with a Line

6.5 Spurious Correlation

   Chapter Summary

   Statistics in Action: Financial Time Series

   Statistics in Action: Executive Compensation




7. Probability

7.1 From Data to Probability

7.2 Rules for Probability

7.3 Independent Events

   Chapter Summary


8. Conditional Probability

8.1 From Tables to Probabilities

8.2 Dependent Events

8.3 O rganizing Probabilities

8.4 O rder in Conditional Probabilities

   Chapter Summary


9. Random Variables

9.1 Random Variables

9.2 Properties of Random Variables

9.3 Properties of Expected Values

9.4 Comparing Random Variables

   Chapter Summary


10. Association between Random Variables

10.1 Portfolios and Random Variables

10.2 Joint Probability Distribution

10.3 Sums of Random Variables

10.4 Dependence between Random Variables

10.5 IID Random Variables

10.6 Weighted Sums

   Chapter Summary


11. Probability Models for Counts

11.1 Random Variables for Counts

11.2 Binomial Model

11.3 Properties of Binomial Random Variables

11.4 Poisson Model

   Chapter Summary


12. The Normal Probability Model

12.1 Normal Random Variable

12.2 The Normal Model

12.3 Percentiles

12.4 Departures from Normality

   Chapter Summary

   Statistics in Action: Managing Financial Risk

   Statistics in Action: Modeling Sampling Variation




13. Samples and Surveys

13.1 Two Surprising Properties of Samples

13.2 Variation

13.3 Alternative Sampling Methods

13.4 Questions to Ask

   Chapter Summary


14. Sampling Variation and Quality

14.1 Sampling Distribution of the Mean

14.2 Control Limits

14.3 Using a Control Chart

14.4 Control Charts for Variation

   Chapter Summary


15. Confidence Intervals

15.1 Ranges for Parameters

15.2 Confidence Interval for the Mean

15.3 Interpreting Confidence Intervals

15.4 Manipulating Confidence Intervals

15.5 Margin of Error

   Chapter Summary


16. Statistical Tests

16.1 Concepts of Statistical Tests

16.2 Testing the Proportion

16.3 Testing the Mean

16.4 Significance versus Importance

16.5 Confidence Interval or Test?

   Chapter Summary


17. Comparison

17.1 Data for Comparisons

17.2 Two-Sample z-test for Proportions

17.3 Two-Sample Confidence Interval for Proportions

17.4 Two-Sample T-test

17.5 Confidence Interval for the Difference between Means

17.6 Paired Comparisons

   Chapter Summary


18. Inference for Counts

18.1 Chi-Squared Tests

18.2 Test of Independence

18.3 General versus Specific Hypotheses

18.4 Tests of Goodness of Fit

   Chapter Summary

   Statistics in Action: Rare Events

   Statistics in Action: Data Mining Using Chi-Squared




19. Linear Patterns

19.1 Fitting a Line to Data

19.2 Interpreting the Fitted Line

19.3 Properties of Residuals

19.4 Explaining Variation

19.5 Conditions for Simple Regression

   Chapter Summary


20. Curved Patterns

20.1 Detecting Nonlinear Patterns

20.2 Transformations

20.3 Reciprocal Transformation

20.4 Logarithm Transformation

   Chapter Summary


21. The Simple Regression Model

21.1 The Simple Regression Model

21.2 Conditions for the SRM

21.3 Inference in Regression

21.4 Prediction Intervals

   Chapter Summary


22. Regression Diagnostics

22.1 Changing Variation

22.2 Outliers

22.3 Dependent Errors and Time Series

   Chapter Summary


23. Multiple Regression

23.1 The Multiple Regression Model

23.2 Interpreting Multiple Regression

23.3 Checking Conditions

23.4 Inference in Multiple Regression

23.5 Steps in Fitting a Multiple Regression

   Chapter Summary


24. Building Regression Models

24.1 Identifying Explanatory Variables

24.2 Collinearity

24.3 Removing Explanatory Variables

   Chapter Summary


25. Categorical Explanatory Variables

25.1 Two-Sample Comparisons

25.2 Analysis of Covariance

25.3 Checking Conditions

25.4 Interactions and Inference

25.5 Regression with Several Groups

   Chapter Summary


26. Analysis of Variance

26.1 Comparing Several Groups

26.2 Inference in ANOVA Regression Models

26.3 Multiple Comparisons

26.4 Groups of Different Size

   Chapter Summary


27. Time Series

27.1 Decomposing a Time Series

27.2 Regression Models

27.3 Checking the Model

   Chapter Summary

   Statistics in Action: Analyzing Experiments

   Statistics in Action: Automated Modeling


Appendix: Tables


Photo Acknowledgments



Supplementary Material (online-only)

Alternative Approaches to Inference

More Regression