Basic Business Statistics: Concepts and Applications, 14th edition

Published by Pearson (January 16, 2018) © 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 business statistics courses.

The statistical foundation to hone analysis skills for real-world decisions

Basic Business Statistics shows students the essential role 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 the 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.

Hallmark features of this title

  • A continuing case throughout the text helps integrate learning across chapters and topics.
  • Digital Cases have students examine interactive documents, sift through various claims, and discover conclusions and claims supported by the data.
  • With an Excel® add-in workbook and unique Excel integration, students can delve into Visual Explorations. These activities demonstrate important statistical concepts in descriptive stats, the normal distribution, sampling distributions, and regression analysis.
  • Consider This essays and Learn More bubbles provide greater insight into the material and raise important issues about the application of statistical knowledge.

New and updated features of this title

  • NEW: A brand new chapter on business analytics makes extensive use of JMP and Minitab to illustrate analytics for the prediction, classification, clustering, and association of data (Ch. 17).
  • UPDATED: Examples and Using Statistics business scenarios draw from all functional areas of business, helping students see how the concepts they're learning apply to their future careers.
  • UPDATED: Emphasis is placed on data analysis and the interpretation of results of a statistical method, rather than the mathematics of that method. JMP results supplement the Excel and Minitab results from previous editions.
  • NEW: Tabular Summaries state hypothesis test and regression example results and conclusions (Chs. 9 to 15).
  • NEW: A First Things First Chapter uses real-world examples to illustrate how developments in the field have made understanding stats even more important (Online Chapter).
  • NEW and UPDATED: New JMP Guides and updated Excel and Minitab Guides provide detailed, hands-on instructions for using the most recent editions of these programs.

Features of MyLab Business Statistics for the 14th Edition

  • StatCrunch, a powerful, web-based statistical software, is integrated into MyLab so students can quickly and easily analyze data sets from their text and exercises.
  • Diverse Question Libraries: From Getting Ready questions to the Conceptual Question Library, we have your assessment needs covered from the mechanics to the critical understanding of stats. The exercise libraries include technology-led instruction, including new Excel-based exercises, and learning aids to reinforce your students' success.
  • Tutorials and Study Cards for Statistical Software: Tutorials provide brief video walkthroughs and step-by-step instructional study cards on common statistical procedures such as confidence interval estimation, ANOVA, regression, and hypothesis testing. Tutorials and study cards are supplied for Excel 2013 and 2016, Excel with PHStat, JMP, and Minitab.
  • The Study Plan gives students personalized recommendations, practice opportunities and learning aids to help them stay on track.
  • The Gradebook offers an easy way for you and your students to see their performance in your course.
  • 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)

About our authors

Mark L. Berenson is Professor of Information Management and Business Analytics at Montclair State University and Professor Emeritus of Information Systems and Statistics at Baruch College. He currently teaches graduate and undergraduate courses in statistics and 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 and an MBA in business statistics from City College of New York and a PhD in business from the City University of New York. Berenson's 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 has coauthored numerous statistics texts published by Pearson. Over the years, Berenson has received several awards for teaching and for innovative contributions to statistics education. In 2005, he was the first recipient of the Catherine A. Becker Service for Educational Excellence Award at Montclair State University and, in 2012, he was the recipient of the Khubani/Telebrands Faculty Research Fellowship in the School of Business.

David Levine, Professor Emeritus of Statistics and CIS at Baruch College, CUNY, has been a nationally recognized innovator in statistics education for more than 3 decades. Levine has coauthored 14 books, including several business statistics textbooks; textbooks and professional titles that explain and explore quality management and the Six Sigma approach; and, with David Stephan, a trade paperback that explains statistical concepts to a general audience. Levine has presented or chaired numerous sessions about business education at leading conferences conducted by the Decision Sciences Institute (DSI) and the American Statistical Association, and he and his coauthors have been active participants in the annual DSI Data, Analytics, and Statistics Instruction (DASI) mini-conference.

During his many years teaching at Baruch College, Levine was recognized for his contributions to teaching and curriculum development with the College's highest distinguished teaching honor. He earned BBA and MBA degrees from CCNY, and a PhD in industrial engineering and operations research from New York 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, non-business, and academic communities, with particular interest in the areas of education, medicine, and nonprofit 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 BS from SUNY-Albany, an MS in statistics from the Wharton School of the University of Pennsylvania, and a PhD degree in statistics, with a cognate in operations research, from the Wharton School of the University of Pennsylvania.

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). An early 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 (formerly MSMESB) mini-conferences, sometimes with his coauthors. Stephan earned a BA from Franklin & Marshall College and an MS from Baruch College, CUNY, and completed the instructional technology graduate program at Teachers College, Columbia University.

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