# Business Statistics, 2nd edition

Published by Pearson (January 9, 2014) © 2015

**Robert A. Donnelly**

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## MyLab

- Reach every student with personalized support
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- Optimize learning with dynamic study tools

**MyStatLab ^{™}** provides

**engaging experiences**that personalize, stimulate, and measure learning for each student.

**Tutorial Exercises with Multimedia Learning Aids:**The homework and practice exercises in MyStatLab align with the exercises in the textbook, and they regenerate algorithmically to give students unlimited opportunity for practice and mastery. Exercises offer immediate helpful feedback, guided solutions, sample problems, animations, videos, and eText clips for extra help at point-of-use.**Additional Statistics Question Libraries:**In addition to algorithmically regenerated questions that are aligned with your textbook, MyStatLab courses come with two additional question libraries.**450****Getting Ready for Statistics**questions offer the developmental math topics students need for the course. These can be assigned as a prerequisite to other assignments, if desired.**1000****Conceptual Question Library**require students to apply their statistical understanding.**NEW! StatCrunch™:**MyStatLab includes a web-based statistical software, StatCrunch, within the online assessment platform so that students can easily analyze data sets from exercises and the text. In addition, MyStatLab includes access to**www.StatCrunch.com,**a website where users can access more than thirteen thousand shared data sets, conduct online surveys, perform complex analyses using the powerful statistical software, and generate compelling reports.**Integration of Statistical Software:**Knowing that students often use external statistical software, we make it easy to copy our data sets, both from the ebook and the MyStatLab questions, into software such as StatCrunch, Minitab, Excel, and more. Students have access to a variety of support tools—Technology Instruction Videos, Technology Study Cards, and Manuals for select titles—to learn how to effectively use statistical software.**Business Insight Videos:**Ten engaging videosshow managers at top companies using statistics in their everyday work. Assignable questions encourage debate and discussion.**StatTalk Videos:**Fun-loving statistician Andrew Vickers takes to the streets of Brooklyn, NY to demonstrate important statistical concepts through interesting stories and real-life events. This series of 24 videos will actually help you understand statistics. Accompanying assessment questions and instructor’s guide available.**Expert Tutoring:**Although many students describe the whole of MyStatLab as “like having your own personal tutor,” students also have access to live tutoring from Pearson. Qualified statistics instructors provide tutoring sessions for students via MyStatLab.

**Business statistics made accessible:** Donnelly’s conversational writing style, friendly step-by-step approach, clearly presented concepts, and skillful use of business-focused examples give meaning to business statistics for today’s college students. From the moment they open the book, students get the sense of sitting down and having a conversation with the author.

**The engaging, straightforward tone**pulls students into the material, without talking down, and helps them understand the concepts even before they realize they’re learning.**The look and feel of the book**is also designed to be friendly and unintimidating.- Key concepts—and why students need to know them—are effectively explained.
**Author comments**in the margins call out quick tips and common mistakes to help clarify specific topics. Presented as informally written bubbles, they’re analogous to side comments instructors would make to students during a lecture to help them understand the material.**Highlighted text**ensures that students take notice of important points.

**How statistics works—in the classroom and in the real world:** Students see why the concepts they’re learning are important and how they will be used in everyday life.

**The “Learn It, Do It, Check It” cycle**lets students learn by reading an example, work in a similar problem on their own, and then check their answer to conform they understand.**A step-by-step approach to complicated problems**breaks down the tougher topics and shows students the steps involved in small, bite-size portions of information.**Your Turn boxes**follow the examples and give students a chance to practice a problem right after they’ve learned about it.**Answers to the Your Turn boxes**appear at the ends of chapters so students can check their work.**Statistics in Practice boxes**use pertinent examples to grab students’ attention,clarify the concepts and show how statistics is used in today’s business environment.**Current business examples**are used throughout to grab and keep students’ interest.- Chapter features ensure understanding before students move on.
**NEW! Learning Objectives**open every chapter.**Detailed end-of-chapter problems**vary in difficulty level and type and provide instructors with flexibility.**Equations sections**provide useful summaries of formulas.

**Updates to this edition** include the most current thinking and practices in the field.

**NEW! Updated technology coverage includes Microsoft Excel 2013,**with instructions for Excel 2010 provided online as needed. Step by step instructions for Mac and Excel 2010 users are on the text’s web site: www.pearsonhighered.com/donnelly.**NEW! More problems—25% more than in the previous edition**, for a total of over 1,110 business-related problems, 35% of which are new or updated.**NEW! Twice as many data sets—over 340**—included in the problems, examples, and Your Turn problems.**NEW! Excel functions**are now used to determine p-values and critical scores for hypothesis tests that use the normal, student’s t, F, and chi-square distributions, giving students more options for this type of analysis.**NEW! Streamlined procedures**include the removal of critical sample mean and critical sample proportion as optional steps to hypothesis testing in Chapters 9 and 10. These two topics are now included in the section describing Type II Errors at the end of Chapter 9.**NEW! Two new chapters**cover Decision Analysis (Chapter 17) and Nonparametric Statistics (Chapter 18). These are available online.

**New and Updated Features**

**Learning Objectives**open every chapter.**StatCrunch™:**MyStatLab includes a web-based statistical software, StatCrunch, within the online assessment platform so that students can easily analyze data sets from exercises and the text. In addition, MyStatLab includes access to**www.StatCrunch.com,**a website where users can access more than thirteen thousand shared data sets, conduct online surveys, perform complex analyses using the powerful statistical software, and generate compelling reports.**Updates to this edition**include the most current thinking and practices in the field.**Updated technology coverage includes Microsoft Excel 2013,**with instructions for Excel 2010 provided online as needed. Step by step instructions for Mac and Excel 2010 users are on the text’s web site: www.pearsonhighered.com/donnelly.**More problems—25% more than in the previous edition**, for a total of over 1,110 business-related problems, 35% of which are new or updated.**Twice as many data sets—over 340**—included in the problems, examples, and Your Turn problems.**Excel functions**are now used to determine p-values and critical scores for hypothesis tests that use the normal, student’s t, F, and chi-square distributions, giving students more options for this type of analysis.**Streamlined procedures**include the removal of critical sample mean and critical sample proportion as optional steps to hypothesis testing in Chapters 9 and 10. These two topics are now included in the section describing Type II Errors at the end of Chapter 9.

**Content Updates**

**Two new chapters**cover Decision Analysis (Chapter 17) and Nonparametric Statistics (Chapter 18). These are available online**.****A new Chapter 17, Decision Analysis**, provides a detailed discussion of decision making under uncertainty and decision making under risk, along with a step-by-step description on the construction and analysis of decision trees.**A new Chapter 18, Nonparametric Statistics**, looks at the following procedures: Sign Test, Wilcoxon Rank-Sum Test, Wilcoxon Signed-Rank Test, Kruskal-Wallis One-Way ANOVA, and Spearman Rank-Order Correlation Coefficient.**New topics of covariance and the correlation of coefficient**introduced at the end of Chapter 3, Calculating Descriptive statistics. The correlation coefficient is also covered in Chapter 14, Correlation and Simple Regression.**Additional features**new to this edition make a good text even better:- Index of Applications
- Redesigned end-of-chapter sections
- Learning Objectives added to chapter openers

Preface

Acknowledgments

Dear Students

**1. An Introduction to Business Statistics**

1.1 Business Statistics and Their Uses

1.2 Data

1.3 Descriptive and Inferential Statistics

1.4 Ethics and Statistics—It’s a Dangerous World of Data Out There

**2. Displaying Descriptive Statistics**

2.1 The Role Technology Plays in Statistics

2.2 Displaying Quantitative Data

2.3 Displaying Qualitative Data

2.4 Contingency Tables

2.5 Stem and Leaf Display

2.6 Scatter Plots

**3. Calculating Descriptive Statistics**

3.1 Measures of Central Tendency

3.2 Measures of Variability

3.3 Using the Mean and Standard Deviation Together

3.4 Working with Grouped Data

3.5 Measures of Relative Position

3.6 Measures of Association Between Two Variables

**4. Introduction to Probabilities**

4.1 An Introduction to Probabilities

4.2 Probability Rules for More Than One Event

4.3 Counting Principles

**5. Discrete Probability Distributions**

5.1 Introduction to Discrete Probability Distributions

5.2 Binomial Distributions

5.3 Poisson Distributions

5.4 The Hypergeometric Distribution

**6. Continuous Probability Distributions**

6.1 Continuous Random Variables

6.2 Normal Probability Distributions

6.3 Exponential Probability Distributions

6.4 Uniform Probability Distributions

**7. Sampling and Sampling Distributions**

7.1 Why Sample?

7.2 Types of Sampling

7.3 Sampling and Nonsampling Errors

7.4 The Central Limit Theorem

7.5 The Sampling Distribution of the Proportion

**8. Confidence Intervals**

8.1 Point Estimates

8.2 Calculating Confidence Intervals for the Mean when the Standard Deviation (σ) of a Population Is Known

8.3 Calculating Confidence Intervals for the Mean when the Standard Deviation (σ) of a Population Is Unknown

8.4 Calculating Confidence Intervals for Proportions

8.5 Determining the Sample Size

8.6 Calculating Confidence Intervals for Finite Populations

**9. Hypothesis Testing for a Single Population**

9.1 An Introduction to Hypothesis Testing

9.2 Hypothesis Testing for the Population Mean When σ Is Known

9.3 Hypothesis Testing for the Population Mean when σ Is Unknown

9.4 Hypothesis Testing for the Proportion of a Population

9.5 Type II Errors

**10. Hypothesis Tests Comparing Two Populations**

10.1 Comparing Two Population Means with

10.2 Comparing Two Population Means with

10.3 Hypothesis Testing With Dependent Samples

10.4 Comparing Two Population Proportions with Independent Samples

**11. Analysis of Variance (ANOVA) Procedures**

11.1 One-Way ANOVA: Examining the Effect a Single Factor Has on the Means of Populations

11.2 Randomized Block ANOVA: Examining the Effects of a Single Factor by Blocking a Second Factor

11.3 Two-Way ANOVA: Examining the Effects Two Factors Have on the Means of Populations

**12. Chi-Square Tests**

12.1 Comparing Two or More Population Proportions

12.2 Determining If Observed Frequencies Follow a Known Probability Distribution

12.3 Testing the Independence of Two Variables

**13. Hypothesis Tests for the Population Variance**

13.1 Testing the Variance of a Single Population

13.2 Comparing the Variances of Two Populations

**14. Correlation and Simple Linear Regression**

14.1 Dependent and Independent Variables

14.2 Correlation Analysis

14.3 Simple Linear Regression Analysis

14.4 Using a Regression to Make a Prediction

14.5 Testing the Significance of the Slope of the Regression Equation

14.6 Assumptions for Regression Analysis

14.7 A Simple Regression Example with a Negative Correlation

14.8 Some Final (but Very Important) Thoughts

**15. Multiple Regression and Model Building**

15.1 Developing the Multiple Regression Model

15.2 Explaining the Variation of the Dependent Variable

15.3 Inferences about the Independent Variables

15.4 Using Qualitative Independent Variables

15.5 Model Building

**16. Forecasting**

16.1 Introduction to Forecasting

16.2 Smoothing Forecasting Methods

16.3 Forecasting with Regression Analysis

16.4 Forecasting with Seasonality

**17. Decision Analysis**

17.1 Introduction to Decision Analysis

17.2 Constructing a Decision Table

17.3 Decision Making Under Uncertainty

17.4 Decision Making Under Risk

17.5 Decision Making Using Decision Trees

17.6 Using Bayes’ Theorem to Calculate Posterior Probabilities

**18. Nonparametric Statistics**

18.1 Introduction to Nonparametric Statistics

18.2 The Sign Test

18.3 The Wilcoxon Rank-Sum Test for Two Independent Samples

18.4 The Wilcoxon Signed-Rank Test for Two Dependent Samples

18.5 The Kruskal-Wallis One-Way ANOVA

18.6 The Spearman Rank-Order Correlation Coefficient

**Appendix A**

Table 1 Binomial Probabilities

Table 2 Poisson Probabilities

Table 3 Cumulative Probabilities for the Standard Normal Distribution

Table 4 Cumulative Probabilities for the Standard Normal Distribution

Table 5 Student’s *t*-distribution

Table 6 *F*-distribution

Table 7 Critical Values of the Studentized Range, *Q*

Table 8 Chi–Square Distribution

Table 9 Critical Values for the Durbin-Watson Statistic

**Appendix B:** Answers to Selected Even-Numbered Problems

Index of Applications

Index

**Bob Donnelly** is a professor at Goldey-Beacom College in Wilmington Delaware with more than 25 years of teaching experience. He teaches classes in statistics, operations management, management information systems, and database management at both the undergraduate and graduate level. Bob earned an undergraduate degree in chemical engineering from the University of Delaware, after which he worked for several years as an engineer with the Diamond Shamrock Corporation in a chlorine plant. Despite success in this field, Bob felt drawn to purse a career in education. It was his desire to teach that took him back to school to earn his MBA and Ph.D. in Operations Research, also from the University of Delaware. Bob also teaches in the MBA program at the International School of Management in Paris, France. He thoroughly enjoys discussing research methods and business statistics with both his French and American students.

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