This book is ideal for a one-semester course in business statistics, offering a streamlined presentation of Business Statistics, by Sharpe, De Veaux, and Velleman .
Better Decisions, Better Results.
In Business Statistics: A First Course, the authors leverage their unique blend of teaching, consulting, and entrepreneurial experiences to bring a modern business edge and dynamic approach to teaching statistics to business students. Focusing on statistics in the context of real business issues, the text emphasizes analysis and understanding over computation. This approach helps students be analytical, preparing them to make better business decisions and effectively communicate results. The authors have an accessible and compelling writing style and use short, targeted chapters to build understanding of new topics. They integrate current business applications to capture students’ attention and teach statistical concepts needed in the modern business world.
The Second Edition provides a wealth of examples and exercises so that the story is always tied to the way statistics is used to make better business decisions. New to this edition are For Examples (illustrative examples), Section Exercises (single-concept exercises), and part-ending Case Studies (which are more in-depth than the Brief Cases located at the end of chapters). To help students become proficient with technology, the Second Edition includes instructions for JMP®, Minitab®, and SPSS®, as well as new and expanded coverage of Excel® 2010 and the add-in XLSTAT ™ for Pearson. Screenshots of output are included throughout the chapters.
This text is also available with MyStatLab™¿—see the Features section or visit www.mystatlab.com for more information. Product Description
In Business Statistics: A First Course, the authors leverage their unique blend of teaching, consulting, and entrepreneurial experiences to bring a modern business edge and dynamic approach to teaching statistics to business students. Focusing on statistics in the context of real business issues, the text emphasizes analysis and understanding over computation. This approach helps students be analytical, preparing them to make better business decisions and effectively communicate results. The authors have an accessible and compelling writing style and use short, targeted chapters to build understanding of new topics. They integrate current business applications to capture students’ attention and teach statistical concepts needed in the modern business world.
The Second Edition provides a wealth of examples and exercises so that the story is always tied to the way statistics is used to make better business decisions. New to this edition are For Examples (illustrative examples), Section Exercises (single-concept exercises), and part-ending Case Studies (which are more in-depth than the Brief Cases located at the end of chapters). To help students become proficient with technology, the Second Edition includes instructions for JMP®, Minitab®, and SPSS®, as well as new and expanded coverage of Excel® 2010 and the add-in XLSTAT ™ for Pearson. Screenshots of output are included throughout the chapters. Features + Benefits
Preparation for the Business World: the authors’ main goal is to prepare students to be successful in the business world by providing them with statistical tools to make informed decisions.
Real data are essential for demonstrating the relevance of statistics in business. Hundreds of exercises, examples, and applications are based on current events and well-known companies, engaging readers with compelling data and scenarios. Students learn from the authors’ consulting experience and see how statistical thinking is vital to modern business decision making.
Chapter Openers present a statistical issue in a managerial setting from a well-known company. These scenarios use real data to demonstrate how statistics relates to business disciplines such as marketing, finance, and economics.
Brief Cases 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.
Case Studies at the end of each part of the text give students experience working through in-depth applications using real data (found on the CD-ROM) and scenarios from actual companies.
A focus on checking assumptions and conditions when using statistical procedures is emphasized throughout the text and examples.
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 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.
Practice and Support: study tools throughout the text prepare students to analyze and interpret data.
NEW! For Example—short, illustrative examples are added to most sections to solidify understanding of newly learned statistical methods and concepts.
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.
Just Checking questions throughout each chapter ask students to stop and think about what they’ve just read. These questions involve little to no calculation. Answers are provided at the end of the chapter so students can check their work.
What Have We Learned? sections at the end of each chapter 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. Each exercise set starts with single-concept exercises, identified by section. Then, the exercises incorporate a straightforward application of the chapter ideas. Next, they tackle larger problems that ask students to work through the logic of a complete analysis. Finally, students are asked to synthesize and incorporate their own ideas.
NEW! Basic Section Exercises have been added to ensure that students are comfortable with the requisite skills before moving on to more involved exercises.
Technology Integration: optional coverage helps students use real statistics software, so they can spend less time learning commands and more time learning the concepts.
Technology Help chapter sections offer guidance on using the most common statistics packages (Excel® 2010, XLStat for Pearson, Minitab®, JMP®, and SPSS®) to practice concepts in the chapters and get started with the technology of their choice.
MyStatLab™: Thecourse that accompanies this new edition includes increased and updated coverage from the text.
NEW! More algorithmically-generated questions are now available. These are closely aligned with the book exercises to give students more diverse practice opportunities.
A library of 1,000 Conceptual Questions requires students to apply their statistical understanding to conceptual business questions.
Technology tutorial videos are available for select exercises to support software usage.
Business Insight Videos show students how statistical methods have been used to solve problems in the business world by companies including Southwest Airlines and Starwood Hotels. Assignable questions are available.
NEW! StatTalk Videos present statistical concepts through a series of fun, brief, real-world examples, with assignable questions.
Preface
Index of Applications
PART I. EXPLORING AND UNDERSTANDING DATA
1. Stats Starts Here!
1.1 What Is Statistics?
1.2 Data
1.3 Variables
2. Displaying and Describing Categorical Data
2.1 Summarizing and Displaying a Single Categorical Variable
2.2 Exploring the Relationship Between Two Categorical Variables
3. Displaying and Summarizing Quantitative Data
3.1 Displaying Quantitative Variables
3.2 Shape
3.3 Center
3.4 Spread
3.5 Boxplots and 5-Number Summaries
3.6 The Center of Symmetric Distributions: The Mean
3.7 The Spread of Symmetric Distributions: The Standard Deviation
3.8 Summary—What to Tell About a Quantitative Variable
4. Understanding and Comparing Distributions
4.1 Comparing Groups with Histograms
4.2 Comparing Groups with Boxplots
4.3 Outliers
4.4 Timeplots: Order, Please!
4.5 Re-expressing Data: A First Look
5. The Standard Deviation as a Ruler and the Normal Model
5.1 Standardizing with z-Scores
5.2 Shifting and Scaling
5.3 Normal Models
5.4 Finding Normal Percentiles
5.5 Normal Probability Plots
Review of Part I. Exploring and Understanding Data
PART II. EXPLORING RELATIONSHIPS BETWEEN VARIABLES
6. Scatterplots, Association, and Correlation
6.1 Scatterplots
6.2 Correlation
6.3 Warning: Correlation ≠ Causation
6.4 Straightening Scatterplots
7. Linear Regression
7.1 Least Squares: The Line of "Best Fit"
7.2 The Linear Model
7.3 Finding the Least Squares Line
7.4 Regression to the Mean
7.5 Examining the Residuals
7.6 R2—The Variation Accounted for by the Model
7.7 Regression Assumptions and Conditions
8. Regression Wisdom
8.1 Examining Residuals
8.2 Extrapolation: Reaching Beyond the Data
8.3 Outliers, Leverage, and Influence
8.4 Lurking Variables and Causation
8.5 Working with Summary Values
Review of Part II. Exploring Relationships Between Variables
PART III. GATHERING DATA
9. Understanding Randomness
9.1 What is Randomness?
9.2 Simulating By Hand
10. Sample Surveys
10.1 The Three Big Ideas of Sampling
10.2 Populations and Parameters
10.3 Simple Random Samples
10.4 Other Sampling Designs
10.5 From the Population to the Sample: You Can't Always Get What You Want
10.6 The Valid Survey
10.7 Common Sampling Mistakes, or How to Sample Badly
11. Experiments and Observational Studies
11.1 Observational Studies
11.2 Randomized, Comparative Experiments
11.3 The Four Principles of Experimental Design
11.4 Control Treatments
11.5 Blocking
11.6 Confounding
Review of Part III Gathering Data
PART IV. RANDOMNESS AND PROBABILITY
12. From Randomness to Probability
12.1 Random Phenomena
12.2 Modeling Probability
12.3 Formal Probability
13. Probability Rules!
13.1 The General Addition Rule
13.2 Conditional Probability and the General Multiplication Rule
13.3 Independence
13.4 Picturing Probability: Tables, Venn Diagrams and Trees
13.5 Reversing the Conditioning and Bayes' Rule
14. Random Variables and Probability Models
14.1 Expected Value: Center
14.2 Standard Deviation
14.3 Combining Random Variables
14.4 The Binomial Model
14.5 Modeling the Binomial with a Normal Model
*14.6 The Poisson Model
14.7 Continuous Random Variables
Review of Part IV Randomness and Probability
PART V. FROM THE DATA AT HAND TO THE WORLD AT LARGE
15. Sampling Distribution Models
15.1 Sampling Distribution of a Proportion
15.2 When Does the Normal Model Work? Assumptions and Conditions
15.3 The Sampling Distribution of Other Statistics
15.4 The Central Limit Theorem: The Fundamental Theorem of Statistics
15.5 Sampling Distributions: A Summary
16. Confidence Intervals for Proportions
16.1 A Confidence Interval
16.2 Interpreting Confidence Intervals: What Does 95% Confidence Really Mean?
16.3 Margin of Error: Certainty vs. Precision
16.4 Assumptions and Conditions
17. Testing Hypotheses About Proportions
17.1 Hypotheses
17.2 P-Values
17.3 The Reasoning of Hypothesis Testing
17.4 Alternative Alternatives
17.5 P-Values and Decisions: What to Tell About a Hypothesis Test
18. Inferences About Means
18.1: Getting Started: The Central Limit Theorem (Again)
18.2: Gosset's t
18.3 Interpreting Confidence Intervals
18.4 A Hypothesis Test for the Mean
18.5 Choosing the Sample Size
19. More About Tests and Intervals
19.1 Choosing Hypotheses
19.2 How to Think About P Values
19.3 Alpha Levels
19.4 Practical vs. Statistical Significance
19.5 Critical Values Again
19.6 Errors
19.7 Power
Review of Part V From the Data at Hand to the World at Large
PART VI. LEARNING ABOUT THE WORLD
20. Comparing Groups
20.1 The Variance of a Difference
20.2 The Standard Deviation of the Difference Between Two Proportions
20.3 Assumptions and Conditions for Comparing Proportions
20.4 The Sampling Distribution of the Difference between Two Proportions
20.5 Comparing Two Means
20.6 The Two-Sample t-Test: Testing for the Difference Between Two Means
20.7 The Two Sample z-Test: Testing for the Difference between Proportions
20.8 The Pooled t-Test: Everyone into the Pool?
20.9 Pooling
21. Paired Samples and Blocks
21.1 Paired Data
21.2 Assumptions and Conditions
21.3 Confidence Intervals for Matched Pairs
21.4 Blocking
22. Comparing Counts
22.1 Goodness-of-Fit Tests
22.2 Chi-Square Test of Homogeneity
22.3 Examining the Residuals
22.4 Chi-Square Test of Independence
23. Inferences for Regression
23.1 The Population and the Sample
23.2 Assumptions and Conditions
23.3 Intuition About Regression Inference
23.4 Regression Inference
23.5 Standard Errors for Predicted Values
23.6 Confidence Intervals for
Predicted Values
23.7* Logistic Regression
Review of Part VI. Learning About the World
PART VII. INFERENCE WHEN VARIABLES ARE RELATED
24. Analysis of Variance
24.1 Testing Whether the Means of Several Groups Are Equal
24.2 The ANOVA Table
24.3 Plot the Data . . .
24.4 Comparing Means
25. Multiple Regression
25.1 Two Predictors
25.2 What Multiple Regression Coefficients Mean
25.3 The Multiple Regression Model
25.4 Multiple Regression Inference
25.5 Comparing Multiple Regression Models
Appendices
A. Answers
Better Decisions, Better Results.
In Business Statistics: A First Course, the authors leverage their unique blend of teaching, consulting, and entrepreneurial experiences to bring a modern business edge and dynamic approach to teaching statistics to business students. Focusing on statistics in the context of real business issues, the text emphasizes analysis and understanding over computation. This approach helps students be analytical, preparing them to make better business decisions and effectively communicate results. The authors have an accessible and compelling writing style and use short, targeted chapters to build understanding of new topics. They integrate current business applications to capture students’ attention and teach statistical concepts needed in the modern business world.
The Second Edition provides a wealth of examples and exercises so that the story is always tied to the way statistics is used to make better business decisions. New to this edition are For Examples (illustrative examples), Section Exercises (single-concept exercises), and part-ending Case Studies (which are more in-depth than the Brief Cases located at the end of chapters). To help students become proficient with technology, the Second Edition includes instructions for JMP®, Minitab®, and SPSS®, as well as new and expanded coverage of Excel® 2010 and the add-in XLSTAT ™ for Pearson. Screenshots of output are included throughout the chapters.
This text is also available with MyStatLab™¿—see the Features section or visit www.mystatlab.com for more information. Product Description
In Business Statistics: A First Course, the authors leverage their unique blend of teaching, consulting, and entrepreneurial experiences to bring a modern business edge and dynamic approach to teaching statistics to business students. Focusing on statistics in the context of real business issues, the text emphasizes analysis and understanding over computation. This approach helps students be analytical, preparing them to make better business decisions and effectively communicate results. The authors have an accessible and compelling writing style and use short, targeted chapters to build understanding of new topics. They integrate current business applications to capture students’ attention and teach statistical concepts needed in the modern business world.
The Second Edition provides a wealth of examples and exercises so that the story is always tied to the way statistics is used to make better business decisions. New to this edition are For Examples (illustrative examples), Section Exercises (single-concept exercises), and part-ending Case Studies (which are more in-depth than the Brief Cases located at the end of chapters). To help students become proficient with technology, the Second Edition includes instructions for JMP®, Minitab®, and SPSS®, as well as new and expanded coverage of Excel® 2010 and the add-in XLSTAT ™ for Pearson. Screenshots of output are included throughout the chapters. Features + Benefits
Preparation for the Business World: the authors’ main goal is to prepare students to be successful in the business world by providing them with statistical tools to make informed decisions.
Real data are essential for demonstrating the relevance of statistics in business. Hundreds of exercises, examples, and applications are based on current events and well-known companies, engaging readers with compelling data and scenarios. Students learn from the authors’ consulting experience and see how statistical thinking is vital to modern business decision making.
Chapter Openers present a statistical issue in a managerial setting from a well-known company. These scenarios use real data to demonstrate how statistics relates to business disciplines such as marketing, finance, and economics.
Brief Cases 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.
Case Studies at the end of each part of the text give students experience working through in-depth applications using real data (found on the CD-ROM) and scenarios from actual companies.
A focus on checking assumptions and conditions when using statistical procedures is emphasized throughout the text and examples.
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 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.
Practice and Support: study tools throughout the text prepare students to analyze and interpret data.
NEW! For Example—short, illustrative examples are added to most sections to solidify understanding of newly learned statistical methods and concepts.
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.
Just Checking questions throughout each chapter ask students to stop and think about what they’ve just read. These questions involve little to no calculation. Answers are provided at the end of the chapter so students can check their work.
What Have We Learned? sections at the end of each chapter 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. Each exercise set starts with single-concept exercises, identified by section. Then, the exercises incorporate a straightforward application of the chapter ideas. Next, they tackle larger problems that ask students to work through the logic of a complete analysis. Finally, students are asked to synthesize and incorporate their own ideas.
NEW! Basic Section Exercises have been added to ensure that students are comfortable with the requisite skills before moving on to more involved exercises.
Technology Integration: optional coverage helps students use real statistics software, so they can spend less time learning commands and more time learning the concepts.
Technology Help chapter sections offer guidance on using the most common statistics packages (Excel® 2010, XLStat for Pearson, Minitab®, JMP®, and SPSS®) to practice concepts in the chapters and get started with the technology of their choice.
MyStatLab™: Thecourse that accompanies this new edition includes increased and updated coverage from the text.
NEW! More algorithmically-generated questions are now available. These are closely aligned with the book exercises to give students more diverse practice opportunities.
A library of 1,000 Conceptual Questions requires students to apply their statistical understanding to conceptual business questions.
Technology tutorial videos are available for select exercises to support software usage.
Business Insight Videos show students how statistical methods have been used to solve problems in the business world by companies including Southwest Airlines and Starwood Hotels. Assignable questions are available.
NEW! StatTalk Videos present statistical concepts through a series of fun, brief, real-world examples, with assignable questions.
Preface
Index of Applications
PART I. EXPLORING AND UNDERSTANDING DATA
1. Stats Starts Here!
1.1 What Is Statistics?
1.2 Data
1.3 Variables
2. Displaying and Describing Categorical Data
2.1 Summarizing and Displaying a Single Categorical Variable
2.2 Exploring the Relationship Between Two Categorical Variables
3. Displaying and Summarizing Quantitative Data
3.1 Displaying Quantitative Variables
3.2 Shape
3.3 Center
3.4 Spread
3.5 Boxplots and 5-Number Summaries
3.6 The Center of Symmetric Distributions: The Mean
3.7 The Spread of Symmetric Distributions: The Standard Deviation
3.8 Summary—What to Tell About a Quantitative Variable
4. Understanding and Comparing Distributions
4.1 Comparing Groups with Histograms
4.2 Comparing Groups with Boxplots
4.3 Outliers
4.4 Timeplots: Order, Please!
4.5 Re-expressing Data: A First Look
5. The Standard Deviation as a Ruler and the Normal Model
5.1 Standardizing with z-Scores
5.2 Shifting and Scaling
5.3 Normal Models
5.4 Finding Normal Percentiles
5.5 Normal Probability Plots
Review of Part I. Exploring and Understanding Data
PART II. EXPLORING RELATIONSHIPS BETWEEN VARIABLES
6. Scatterplots, Association, and Correlation
6.1 Scatterplots
6.2 Correlation
6.3 Warning: Correlation ≠ Causation
6.4 Straightening Scatterplots
7. Linear Regression
7.1 Least Squares: The Line of "Best Fit"
7.2 The Linear Model
7.3 Finding the Least Squares Line
7.4 Regression to the Mean
7.5 Examining the Residuals
7.6 R2—The Variation Accounted for by the Model
7.7 Regression Assumptions and Conditions
8. Regression Wisdom
8.1 Examining Residuals
8.2 Extrapolation: Reaching Beyond the Data
8.3 Outliers, Leverage, and Influence
8.4 Lurking Variables and Causation
8.5 Working with Summary Values
Review of Part II. Exploring Relationships Between Variables
PART III. GATHERING DATA
9. Understanding Randomness
9.1 What is Randomness?
9.2 Simulating By Hand
10. Sample Surveys
10.1 The Three Big Ideas of Sampling
10.2 Populations and Parameters
10.3 Simple Random Samples
10.4 Other Sampling Designs
10.5 From the Population to the Sample: You Can't Always Get What You Want
10.6 The Valid Survey
10.7 Common Sampling Mistakes, or How to Sample Badly
11. Experiments and Observational Studies
11.1 Observational Studies
11.2 Randomized, Comparative Experiments
11.3 The Four Principles of Experimental Design
11.4 Control Treatments
11.5 Blocking
11.6 Confounding
Review of Part III Gathering Data
PART IV. RANDOMNESS AND PROBABILITY
12. From Randomness to Probability
12.1 Random Phenomena
12.2 Modeling Probability
12.3 Formal Probability
13. Probability Rules!
13.1 The General Addition Rule
13.2 Conditional Probability and the General Multiplication Rule
13.3 Independence
13.4 Picturing Probability: Tables, Venn Diagrams and Trees
13.5 Reversing the Conditioning and Bayes' Rule
14. Random Variables and Probability Models
14.1 Expected Value: Center
14.2 Standard Deviation
14.3 Combining Random Variables
14.4 The Binomial Model
14.5 Modeling the Binomial with a Normal Model
*14.6 The Poisson Model
14.7 Continuous Random Variables
Review of Part IV Randomness and Probability
PART V. FROM THE DATA AT HAND TO THE WORLD AT LARGE
15. Sampling Distribution Models
15.1 Sampling Distribution of a Proportion
15.2 When Does the Normal Model Work? Assumptions and Conditions
15.3 The Sampling Distribution of Other Statistics
15.4 The Central Limit Theorem: The Fundamental Theorem of Statistics
15.5 Sampling Distributions: A Summary
16. Confidence Intervals for Proportions
16.1 A Confidence Interval
16.2 Interpreting Confidence Intervals: What Does 95% Confidence Really Mean?
16.3 Margin of Error: Certainty vs. Precision
16.4 Assumptions and Conditions
17. Testing Hypotheses About Proportions
17.1 Hypotheses
17.2 P-Values
17.3 The Reasoning of Hypothesis Testing
17.4 Alternative Alternatives
17.5 P-Values and Decisions: What to Tell About a Hypothesis Test
18. Inferences About Means
18.1: Getting Started: The Central Limit Theorem (Again)
18.2: Gosset's t
18.3 Interpreting Confidence Intervals
18.4 A Hypothesis Test for the Mean
18.5 Choosing the Sample Size
19. More About Tests and Intervals
19.1 Choosing Hypotheses
19.2 How to Think About P Values
19.3 Alpha Levels
19.4 Practical vs. Statistical Significance
19.5 Critical Values Again
19.6 Errors
19.7 Power
Review of Part V From the Data at Hand to the World at Large
PART VI. LEARNING ABOUT THE WORLD
20. Comparing Groups
20.1 The Variance of a Difference
20.2 The Standard Deviation of the Difference Between Two Proportions
20.3 Assumptions and Conditions for Comparing Proportions
20.4 The Sampling Distribution of the Difference between Two Proportions
20.5 Comparing Two Means
20.6 The Two-Sample t-Test: Testing for the Difference Between Two Means
20.7 The Two Sample z-Test: Testing for the Difference between Proportions
20.8 The Pooled t-Test: Everyone into the Pool?
20.9 Pooling
21. Paired Samples and Blocks
21.1 Paired Data
21.2 Assumptions and Conditions
21.3 Confidence Intervals for Matched Pairs
21.4 Blocking
22. Comparing Counts
22.1 Goodness-of-Fit Tests
22.2 Chi-Square Test of Homogeneity
22.3 Examining the Residuals
22.4 Chi-Square Test of Independence
23. Inferences for Regression
23.1 The Population and the Sample
23.2 Assumptions and Conditions
23.3 Intuition About Regression Inference
23.4 Regression Inference
23.5 Standard Errors for Predicted Values
23.6 Confidence Intervals for
Predicted Values
23.7* Logistic Regression
Review of Part VI. Learning About the World
PART VII. INFERENCE WHEN VARIABLES ARE RELATED
24. Analysis of Variance
24.1 Testing Whether the Means of Several Groups Are Equal
24.2 The ANOVA Table
24.3 Plot the Data . . .
24.4 Comparing Means
25. Multiple Regression
25.1 Two Predictors
25.2 What Multiple Regression Coefficients Mean
25.3 The Multiple Regression Model
25.4 Multiple Regression Inference
25.5 Comparing Multiple Regression Models
Appendices
A. Answers