Basic Business Statistics, Global Edition, 14th edition
Published by Pearson (June 19, 2019) © 2019
- Mark L. Berenson Zicklin School of Business, City University of New York; Montclair State University
- David M. Levine Baruch College, City University of New York
- Kathryn A. Szabat La Salle University
- David F. Stephan Two Bridges Instructional Technology
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For one- or-two-semester courses in business statistics.
Give students the statistical foundation to hone their analysis skills for real-world decisions
Basic Business Statistics helps students see the essential role that statistics will play in their future careers by using examples drawn from all functional areas of real-world business. Guided by principles set forth by ASA’s Guidelines for Assessment and Instruction (GAISE) reports and the authors’ diverse teaching experiences, the text continues to innovate and improve the way this course is taught to students. The 14th Edition includes new and updated resources and tools to enhance students’ understanding, and provides the best framework for learning statistical concepts.
MyLabTM Business Statistics is not included. Students, if MyLab Business Statistics is a recommended/mandatory component of the course, please ask your instructor for the correct ISBN. MyLab Business Statistics should only be purchased when required by an instructor. Instructors, contact your Pearson representative for more information.
Reach every student by pairing this text with MyLab Business Statistics
MyLabTM is the teaching and learning platform that empowers you to reach every student. By combining trusted author content with digital tools and a flexible platform, MyLab personalizes the learning experience and improves results for each student.
This title is a Pearson Global Edition. The Editorial team at Pearson has worked closely with educators around the world to include content, which is especially relevant to students outside the United States.
Helps students understand the role of statistics in their future careers
· New - This edition contains a new Business Analytics Chapter that makes extensive use of JMP and Minitab to illustrate predictive analytics for prediction, classification, clustering, and association, as well as explaining what text analytics does and how descriptive and prescriptive analytics relate to predictive analytics.
· Updated - Examples and Using Statistics business scenarios are drawn from all functional areas of business, helping students see how the concepts they’re learning apply to their future careers and providing an applied context for learning.
· Project-Detailed Case Studies are included in numerous chapters. The Managing Ashland MultiComm Services continuing case, a team project related to bond funds, and undergraduate and graduate student surveys feature at the end of most chapters, helping to integrate learning across the chapters.
· Digital Cases let students examine interactive PDFs to sift through various claims and information, discover the conclusions and claims supported by the data, and identify common misuses of statistical information.
Gives students a framework to learn and understand statistical concepts
· Updated - This text emphasizes data analysis and the interpretation of the results of a statistical method, rather than focusing on the mathematics of a method. The 14th Edition includes JMP results, supplementing the Excel and Minitab results from previous editions.
· Visual Explorations allow students to interactively explore important statistical concepts in descriptive statistics, the normal distribution, sampling distributions, and regression analysis by using an Excel® add-in workbook and unique Excel integration.
· New - Chapters 9 through 15 now include Tabular Summaries that state hypothesis test and regression example results, along with the conclusions that those results support.
· Features like Consider This essays and Learn More bubbles provide greater insight into the material and raise important issues about the application of statistical knowledge.
Enhances learning with flexible online features and software integration
· Integrates Excel with Visual Explorations that demonstrate basic concepts, and designed and implemented PHStat, the Pearson statistical add-in for Excel that places the focus on statistical learning.
· An extensive online library of separate topics, sections, and two full chapters allows instructors to tailor these materials to meet their curricular needs, and provides opportunities for additional learning.
· New - A First Things First Chapter, available as a complimentary online download, allows students to get a head start on learning and uses real-world examples to illustrate how developments, such as the increasing use of business analytics and “big data,” have made knowing and understanding statistics even more important.
· Updated - New JMP Guides and updated Excel and Minitab Guides provide detailed, hands-on instructions for using the most recent editions of tho
Helps students understand the role of statistics in their future careers
· This edition contains a new Business Analytics Chapter that makes extensive use of JMP and Minitab to illustrate predictive analytics for prediction, classification, clustering, and association, as well as explaining what text analytics does and how descriptive and prescriptive analytics relate to predictive analytics.
· Examples and Using Statistics business scenarios are drawn from all functional areas of business, helping students see how the concepts they’re learning apply to their future careers and providing an applied context for learning.
Gives students a framework to learn and understand statistical concepts
· This text emphasizes data analysis and the interpretation of the results of a statistical method, rather than focusing on the mathematics of a method. The 14th Edition includes JMP results, supplementing the Excel and Minitab results from previous editions.
· Chapters 9 through 15 now include Tabular Summaries that state hypothesis test and regression example results, along with the conclusions that those results support.
Enhances learning with flexible online features and software integration
· A First Things First Chapter, available as a complimentary online download, allows students to get a head start on learning and uses real-world examples to illustrate how developments, such as the increasing use of business analytics and “big data,” have made knowing and understanding statistics even more important.
· New JMP Guides and updated Excel and Minitab Guides provide detailed, hands-on instructions for using the most recent editions of those programs in business decision making, with templates and applications designed to minimize the frustration of using the software and maximize statistical learning. The modularized nature of the software allows instructors and students to switch between applications as they use the book.
MyLabTM Business Statistics is not included. Students, if MyLab Business Statistics is a recommended/mandatory component of the course, please ask your instructor for the correct ISBN. MyLab Business Statistics should only be purchased when required by an instructor. Instructors, contact your Pearson representative for more information.
First Things First (online)
1. Defining and Collecting Data
2. Organizing and Visualizing Variables
3. Numerical Descriptive Measures
4. Basic Probability
5. Discrete Probability Distributions
6. The Normal Distribution and Other Continuous Distributions
7. Sampling Distributions
8. Confidence Interval Estimation
9. Fundamentals of Hypothesis Testing: One-Sample Tests
10. Two-Sample Tests
11. Analysis of Variance
12. Chi-Square and Nonparametric Tests
13. Simple Linear Regression
14. Introduction to Multiple Regression
15. Multiple Regression Model Building
16. Time-Series Forecasting
17. Business Analytics
18. Getting Ready to Analyze Data in the Future
19. Statistical Applications in Quality Management (online)
20. Decision Making (online)
Mark L. Berenson is Professor of Management and Information Systems at Montclair State University (Montclair, New Jersey) and also Professor Emeritus of Statistics and Computer Information Systems at Bernard M. Baruch College (City University of New York). He teaches graduate and undergraduate courses in statistics and in operations management in the School of Business and an undergraduate course in international justice and human rights that he co-developed in the College of Humanities and Social Sciences. Berenson received a BA in economic statistics, an MBA in business statistics from City College of New York and a PhD in business from the City University of New York. His research has been published in Decision Sciences Journal of Innovative Education, Review of Business Research, The American Statistician, Communications in Statistics, Psychometrika, Educational and Psychological Measurement, Journal of Management Sciences and Applied Cybernetics, Research Quarterly, Stats Magazine, The New York Statistician, Journal of Health Administration Education, Journal of Behavioral Medicine and Journal of Surgical Oncology. His invited articles have appeared in The Encyclopedia of Measurement & Statistics and Encyclopedia of Statistical Sciences. He is co-author of 11 statistics texts published by Prentice Hall, including Statistics for Managers Using Microsoft Excel, Basic Business Statistics: Concepts and Applications and Business Statistics: A First Course. Over the years, Berenson has received several awards for teaching and for innovative contributions to statistics education.
David M. Levine is Professor Emeritus of Statistics and Computer Information Systems at Baruch College (City University of New York). He received BBA and MBA degrees in statistics from City College of New York and a PhD from New York University in industrial engineering and operations research. He is nationally recognised as a leading innovator in statistics education and is the co-author of 14 books, including such best-selling statistics textbooks as Statistics for Managers Using Microsoft Excel, Basic Business Statistics: Concepts and Applications, Business Statistics: A First Course and Applied Statistics for Engineers and Scientists Using Microsoft Excel and Minitab. He also is the co-author of Even You Can Learn Statistics: A Guide for Everyone Who Has Ever Been Afraid of Statistics, Six Sigma for Green Belts and Champions and Design for Six Sigma for Green Belts and Champions, and the author of Statistics for Six Sigma Green Belts and Quality Management. He is also the author of Video Review of Statistics and Video Review of Probability, and the statistics module of the MBA primer published by Cengage Learning. He has published articles in various journals, including Psychometrika, The American Statistician, Communications in Statistics, Decision Sciences Journal of Innovative Education, Multivariate Behavioral Research, Journal of Systems Management, Quality Progress and The American Anthropologist, and he has given numerous talks at the Decision Sciences Institute (DSI), American Statistical Association (ASA) and Making Statistics More Effective in Schools and Business (MSMESB) conferences. Levine has also received several awards for outstanding teaching and curriculum development from Baruch College.
Advances in computing have always shaped David Stephan's professional life. As an undergraduate, he helped professors use statistics software that was considered advanced even though it could compute only several things discussed in Chapter 3, thereby gaining an early appreciation for the benefits of using software to solve problems (and perhaps positively influencing his grades). A nearly advocate of using computers to support instruction, he developed a prototype of a mainframe-based system that anticipated features found today in Pearson's MathXL and served as special assistant for computing to the Dean and Provost at Baruch College. In his many years teaching at Baruch, Stephan implemented the first computer-based classroom, helped redevelop the CIS curriculum, and, as part of a FIPSE project team, designed and implemented a multimedia learning environment. He was also nominated for teaching honors. Stephan has presented at SEDSI and DSI DASI mini-conferences, sometimes with his coauthors. Stephan earned a B.A. from Franklin & Marshall College and an M.S. from Baruch College, CUNY, and completed the instructional technology graduate program at Teachers College, Columbia University.
As Associate Professor of Business Systems and Analytics at La Salle University, Kathryn Szabat has transformed several business school majors into one interdisciplinary major that better supports careers in new and emerging disciplines of data analysis including analytics. Szabat strives to inspire, stimulate, challenge, and motivate students through innovation and curricular enhancements and shares her coauthors' commitment to teaching excellence and the continual improvement of statistics presentations. Beyond the classroom she has provided statistical advice to numerous business, nonbusiness, and academic communities, with particular interest in the areas of education, medicine, and non-profit capacity building. Her research activities have led to journal publications, chapters in scholarly books, and conference presentations. Szabat is a member of the American Statistical Association (ASA), DSI, Institute for Operation Research and Management Sciences (INFORMS), and DSI DASI. She received a B.S. from SUNY-Albany, an M.S. in statistics from the Wharton School of the University of Pennsylvania, and a Ph.D. in statistics, with a cognate in operations research, from the Wharton School of the University of Pennsylvania.
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