Business Statistics, Global Edition

Series
Pearson
Author
Norean R. Sharpe / Richard D. De Veaux / Paul Velleman  
Publisher
Pearson
Cover
Softcover
Edition
3
Language
English
Total pages
992
Pub.-date
September 2014
ISBN13
9781292058696
ISBN
1292058692
Related Titles


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9781292058696
Business Statistics, Global Edition
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Description

For courses in Business Statistics

 

Business Statistics, Third Edition, by Sharpe, De Veaux, and Velleman, narrows the gap between theory and practice–relevant statistical methods empower business students to make effective, data-informed decisions. With their unique blend of teaching, consulting, and entrepreneurial experiences, this dynamic author team brings a modern edge to teaching statistics to business students. Focusing on statistics in the context of real business issues, with an emphasis on analysis and understanding over computation, the text helps students be analytical, prepares them to make better business decisions, and shows them how to effectively communicate results.

 

This program provides a better teaching and learning experience—for you and your students. Here’s how:

  • Grounded in modern business, this text provides a real-world context for statistical concepts, preparing students to be successful in the business world.
  • Practice and support: Study tools throughout the text prepare students to analyze and interpret data.
  • Integrated technology: Optional coverage helps students use real statistics software
  • NEW! Improved organization and a streamlined design make the text more accessible than ever.

Please note that the product you are purchasing does not include MyStatLab.

 

MyStatLab

 

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Features

 

 

  • Grounded in modern business, this text provides a real-world context for statistical concepts, preparing students to be successful in the business world.
    • The authors’ unique blend of teaching, consulting, and entrepreneurial experiences, along with the casual writing style, which is often infused with humor, add to the text’s appeal to today’s students.
      • NEW! Increased focus on core material. Discussions have been tightened to get students into the material as quickly as possible, focusing increasingly n the central ideas and core material.
    • Real data in hundreds of examples, exercises, and applications tie the concepts to the way statistics is used to make better business decisions.
      • Motivating chapter opening vignettes: scenarios using real data to present a statistical issue in a managerial setting from a well-known company in such areas as marketing, finance, and economics
      • Brief Cases at the end of each chapter–using real data and asking students to investigate a question or make a business decision.
      • Case Studies at the end of each part–more in-depth than the brief Cases
      • NEW! Updated examples reflect the changing world and the marked changes in the U.S. and world economies.
    • The emphasis on better statistical thinking trains students to apply statistics correctly.
      • A focus on checking assumptions and conditions when using statistical procedures is emphasized throughout the text and the examples.
      • Ethics in Action vignettes illustrate the judgment needed in statistical analysis. Questions are included for study and reflection.
        • NEW! More than half of the Ethics in Action features are updated. Ethically and statistically sound alternative approaches and a link to the American Statistical Association’s Ethical Guidelines are now presented in the Instructor's Solutions Manual, making the Ethics features suitable for assignment or class discussion.
      • What Can Go Wrong? sections prepare students with the tools they need to detect common statistical errors and offer practice in debunking misuses of statistics.
  • Practice and support: Study tools throughout the text prepare students to analyze and interpret data.
    • 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.
    • Helpful Margin Notes include By Hand boxes break apart the calculation of some of the simpler formulas, Notation Alerts thatcall out special notations, and Math Boxes present the mathematical underpinnings of the statistical methods and concepts.
    • Just Checking questions ask students to stop and think about what they’ve just read. These questions involve little to no calculation, and answers are provided at the end of the chapter so students can check their work.
    • What Have We Learned? chapter summaries provide an overview of the chapter’s concepts through annotated learning objectives and a list of boldface (new) terms and their definitions.
    • Exercises are included within each chapter and progress in difficulty and complexity. 
  • Integrated technology: Optional coverage helps students use real statistics software
    • NEW! Enhanced Technology Help with expanded Excel® 2013 coverage. We've updated Technology Help and added detailed instructions for Excel 2013 to almost every chapter. Increased coverage of Excel includes screenshots and, in Technology Help sections, guidance for using Excel 2010 to demonstrate how to use Excel to perform statistical analysis.
    • Technology Help sections have been updated to reflect the latest technology releases. Technology Help now includes step-by-step guidance for XLSTAT™ for Pearson, an Excel add-in offered (bundled) with the textbook.
    • XLSTAT™ for Pearson is an Excel add-in that enhances the analytical capabilities of Excel. Developed in 1993, XLSTAT is used by leading businesses and universities around the world. XLSTAT is compatible with all Excel versions (except Mac 2008) and is compatible with both Windows® and Mac® systems.
  • NEW! Improved organization and a streamlined design make the text more accessible than ever. While retaining the text’s successful “data first” presentation of topics, the authors have improved the way the book is organized.
    • Chapters 1—4 are streamlined to cover collecting, displaying, summarizing, and understanding data in four chapters, giving students a solid foundation to launch their study of probability and statistics.
    • Chapters 5—9 introduce students to randomness and probability, and then apply these new concepts to sampling as a gateway to the core material on statistical inference. Discussion of probability tees and Bayes’ rule is now in these chapters.
    • Chapters 10—14 cover inference for both proportions and means.
    • Chapters 15—19 cover regression-based models for decision making.
    • Chapters 20—25 discuss special topics that can be selected according to the needs of the course and the instructor’s preferences.

 

New to this Edition

New and Updated in the Text

  • Increased focus on core material. Discussions have been tightened to get students into the material as quickly as possible, focusing increasingly n the central ideas and core material.
  • Updated examples reflect the changing world and the marked changes in the U.S. and world economies.
  • NEW! More than half of the Ethics in Action features are updated. Ethically and statistically sound alternative approaches and a link to the American Statistical Association’s Ethical Guidelines are now presented in the Instructor's Solutions Manual, making the Ethics features suitable for assignment or class discussion.
  • Enhanced Technology Help with expanded Excel® 2013 coverage. We've updated Technology Help and added detailed instructions for Excel 2013 to almost every chapter. Increased coverage of Excel includes screenshots and, in Technology Help sections, guidance for using Excel 2010 to demonstrate how to use Excel to perform statistical analysis.
  • Improved organization and a streamlined design make the text more accessible than ever. While retaining the text’s successful “data first” presentation of topics, the authors have improved the way the book is organized.
    • Chapters 1—4 are streamlined to cover collecting, displaying, summarizing, and understanding data in four chapters, giving students a solid foundation to launch their study of probability and statistics.
    • Chapters 5—9 introduce students to randomness and probability, and then apply these new concepts to sampling as a gateway to the core material on statistical inference. Discussion of probability tees and Bayes’ rule is now in these chapters.
    • Chapters 10—14 cover inference for both proportions and means.
    • Chapters 15—19 cover regression-based models for decision making.
    • Chapters 20—25 discuss special topics that can be selected according to the needs of the course and the instructor’s preferences.

 


Table of Contents

Preface

Index of Applications

 

1. Data and Decisions (E-Commerce)

1.1 Data and Decisions

1.2 Variable Types

1.3 Data Sources: Where, How, and When

   Ethics in Action

   Technology Help: Data on the Computer

   Brief Case: Credit Card Bank

 

2. Displaying and Describing Categorical Data (Keen, Inc.)

2.1 Summarizing a Categorical Variable

2.2 Displaying a Categorical Variable 

2.3 Exploring Two Categorical Variables: Contingency Tables 

2.4 Segmented Bar Charts and Mosaic Plots 

2.5 Simpson's Paradox

   Ethics in Action

   Technology Help: Displaying Categorical Data on the Computer

   Brief Case: Credit Card Bank

 

3. Displaying and Describing Quantitative Data (AIG)

3.1 Displaying Quantitative Variables 

3.2 Shape 

3.3 Center 

3.4 Spread of the Distribution

3.5 Shape, Center, and Spread–A Summary

3.6 Standardizing Variables 

3.7 Five-Number Summary and Boxplots 

3.8 Comparing Groups,

3.9 Identifying Outliers,

3.10 Time Series Plots

3.11 Transforming Skewed Data

   Ethics in Action

   Technology Help: Displaying and Summarizing Quantitative Variables

   Brief Cases: Detecting the Housing Bubble and Socio-Economic Data on States

 

4. Correlation and Linear Regression (Amazon.com)

4.1 Looking at Scatterplots

4.2 Assigning Roles to Variables in Scatterplots

4.3 Understanding Correlation

4.4 Lurking Variables and Causation

4.5 The Linear Model

4.6 Correlation and the Line

4.7 Regression to the Mean

4.8 Checking the Model

4.9 Variation in the Model and R2

4.10 Reality Check: Is the Regression Reasonable?

4.11 Nonlinear Relationships

   Ethics in Action

   Technology Help: Correlation and Regression

   Brief Cases: Fuel Efficiency, Cost of Living, and Mutual Funds

 

   Case Study I: Paralyzed Veterans of America

 

5. Randomness and Probability (Credit Reports and the Fair Isaacs Corporation)

5.1 Random Phenomena and Probability

5.2 The Nonexistent 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

5.8 Probability Trees

5.9 Reversing the Conditioning: Bayes’ Rule

   Ethics in Action

   Technology Help: Generating Random Numbers

   Brief Case

 

6. Random Variables and Probability Models (Metropolitan Life Insurance Company)

6.1 Expected Value of a Random Variable

6.2 Standard Deviation of a Random Variable

6.3 Properties of Expected Values and Variances

6.4 Bernoulli Trials

6.5 Discrete Probability Models

   Ethics in Action

   Technology Help: Random Variables and Probability Models

   Brief Case: Investment Options

 

7. The Normal and other Continuous Distributions (The NYSE)

7.1 The Standard Deviation as a Ruler

7.2 The Normal Distribution

7.3 Normal Probability Plots

7.4 The Distribution of Sums of Normals

7.5 The Normal Approximation for the Binomial

7.6 The Other Continuous Random Variables

   Ethics in Action

   Technology Help: Probability Calculations and Plots

    Brief Case

 

8. Surveys and Sampling (Roper Polls)

8.1 Three Ideas of Sampling

8.2 Populations and Parameters

8.3 Common Sampling Designs

8.4 The Valid Survey

8.5 How to Sample Badly

   Ethics in Action

   Technology Help: Random Sampling

   Brief Cases: Market Survey Research and The GfK Roper Reports Worldwide Survey

 

9. Sampling Distributions and Confidence Intervals for Proportions (Marketing Credit Cards: The MBNA Story)

9.1 The Distribution of Sample Proportions

9.2 A Confidence Interval

9.3 Margin of Error: Certainty vs. Precision

9.4 Choosing and Sample Size

   Ethics in Action

   Technology Help: Confidence Intervals for Proportions

   Brief Case: Real Estate Simulation

 

Case Study II

 

10. Testing Hypotheses about Proportions (Dow Jones Industrial Average)

10.1 Hypotheses

10.2 A Trial as a Hypothesis Test

10.3 P-Values

10.4 The Reasoning of Hypothesis Testing

10.5 Alternative Hypotheses

10.6 p-Values and Decisions: What to Tell About a Hypothesis Test

   Ethics in Action

   Technology Help: Hypothesis Tests

   Brief Cases: Metal Production and Loyalty Program

 

11. Confidence Intervals and Hypothesis Tests for Means (Guinness & Co.)

11.1 The Central Limit Theorem

11.2 The Sampling Distribution of the Mean

11.3 How Sampling Distribution Models Work

11.4 Gossett and the -Distribution

11.5 A Confidence Interval for Means

11.6 Assumptions and Conditions

11.7 Testing Hypothesis about Means–the One-Sample t-Test

   Ethics in Action

   Technology Help: Inference for Means

   Brief Cases: Real Estate and Donor Profiles

 

12. More About Tests and Intervals (Traveler’s Insurance)

12.1 How to Think About P-Values

12.2 Alpha Levels and Significance

12.3 Critical Values

12.4 Confidence Intervals and Hypothesis Tests

12.5 Two Types of Errors

12.6 Power

   Ethics in Action

   Technology Help: Hypothesis Tests

   Brief Case

 

13. Comparing Two Means (Visa Global Organization)

13.1 Comparing 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 Paired Data

13.7 Paired Methods

Ethics in Action

   Technology Help: Two-Sample Methods

   Technology Help: Paired t

   Brief Cases: Real Estate and Consumer Spending Patterns (Data Analysis)

 

14. Inference for Counts: Chi-Square Tests (SAC Capital)

14.1 Goodness-of-Fit Tests

14.2 Interpreting Chi-Square Values

14.3 Examining the Residuals

14.4 The Chi-Square Test of Homogeneity

14.5 Comparing Two Proportions

14.6 Chi-Square Test of Independence

   Ethics in Action

   Technology Help: Chi-Square

   Brief Cases: Health Insurance and Loyalty Program

 

   Case Study III: Investment Strategy Segmentation

 

15. Inference for Regression (Nambé Mills)

15.1 A Hypothesis Test and Confidence Interval for the Slope

15.2 Assumptions and Conditions

15.3 Standard Errors for Predicted Values

15.4 Using Confidence and Prediction Intervals

   Ethics in Action

   Technology Help: Regression Analysis

   Brief Cases: Frozen Pizza and Global Warming?

 

16. Understanding Residuals (Kellogg’s)

16.1 Examining Residuals for Groups

16.2 Extrapolation and Prediction

16.3 Unusual and Extraordinary Observations

16.4 Working with Summary Values

16.5 Autocorrelation

16.6 Transforming (Re-expressing) Data

16.7 The Ladder of Powers

   Ethics in Action

   Technology Help: Examining Residuals

   Brief Cases: Gross Domestic Product and Energy Sources

 

17. Multiple Regression (Zillow.com)

17.1 The Multiple Regression Model

17.2 Interpreting Multiple Regression Coefficients

17.3 Assumptions and Conditions for the Multiple Regression Model

17.4 Testing the Multiple Regression Model

17.5 Adjusted R and the F-statistic

17.6 The Logistic Regression Model

   Ethics in Action

   Technology Help: Regression Analysis

   Brief Case: Golf Success

 

18. Building Multiple Regression Models (Bolliger and Mabillard)

18.1 Indicator (or Dummy) Variables

18.2 Adjusting for Different Slopes–Interaction Terms

18.3 Multiple Regression Diagnostics

18.4 Building Regression Models

18.5 Collinearity

18.6 Quadratic Terms

   Ethics in Action

   Technology Help: Building Multiple Regression Models

   Brief Case

 

19. Time Series Analysis (Whole Food Market)

19.1 What Is a Time Series?

19.2 Components of a Time Series

19.3 Smoothing Methods

19.4 Summarizing Forecast Error

19.5 Autoregressive Models

19.6 Multiples Regression-based Models

19.7 Choosing a Time Series Forecasting Method

19.8 Interpreting Time Series Models: The Whole Foods Data Revisited

   Ethics in Action

   Technology Help

   Brief Cases: Intel Corporation and Tiffany & Co.

 

   Case Study IV: Health Care Costs

 

20. Design and Analysis of Experiments and Observational Studies (Capital One)

20.1 Observational Studies

20.2 Randomized Comparative Experiments

20.3 The Four Principles of Experimental Design

20.4 Experimental Designs

20.5 Issues in Experimental Design

20.6 Analyzing a Design in One Factor–The One-Way Analysis of Variance

20.7 Assumptions and Conditions for ANOVA

20.8 Multiple Comparisons

20.9 ANOVA on Observational Data

20.10 Analysis of Multifactor Designs

   Ethics in Action

   Technology Help: Analysis of Variance

   Brief Case: Multifactor Experiment Design

 

 

21. Quality Control (Sony)

21.1 A Short History of Quality Control

21.2 Control Charts for Individual Observations (Run Charts)

21.3 Control Charts for Measurements: (x-bar) and R Charts

21.4 Actions for Out-of-Control Processes

21.5 Control Charts for Attributes: p Charts and c Charts

21.6 Philosophies of Quality Control

   Ethics in Action

   Technology Help: Quality Control Charts

   Brief Case: Laptop Touchpad Quality

 

22. Nonparametric Methods (i4cp)

22.1 Ranks

22.2 The Wilcoxon Rank-Sum/Mann-Whitney Statistic

22.3 Kruskal-Wallace Test

22.4 Paired Data: The Wilcoxon Signed-Rank Test

22.5 Friedman Test for a Randomized Block Design

22.6 Kendall’s Tau: Measuring Monotonicity

22.7 Spearman’s Rho

22.8 When Should You Use Nonparametric Methods?

   Ethics in Action

   Technology Help

   Brief Case: Real Estate Reconsidered

 

23. Decision Making and Risk (Data Description, Inc.)

23.1 Actions, States of Nature, and Outcomes

23.2 Payoff Tables and Decisions Trees

23.3 Minimizing Loss and Maximizing Gain

23.4 The Expected Value of an Action

23.5 Expected Value with Perfect Information

23.6 Decisions Made with Sample Information

23.7 Estimating Variation

23.8 Sensitivity

23.9 Simulation

23.10 More Complex Decisions

   Ethics in Action

   Technology Help

   Brief Cases: Texaco-Pennzoil and Insurance Services, Revisited

 

24. Introduction to Data Mining (Paralyzed Veterans of America)

24.1 The Big Data Revolution

24.2 Direct Marketing

24.3 The Goals of Data Mining

24.4 Data Mining Myths

24.5 Successful Data Mining

24.6 Data Mining Problems

24.7 Data Mining Algorithms

24.8 The Data Mining Process

24.9 Summary

   Ethics in Action

   Case Study V Marketing Experiment

 

Appendices

 

A. Answers

B. Photo Acknowledgments

C. Tables and Selected Formulas

 

Index