Essentials of Statistics for Business and Economics 7th Edition
David R. Anderson | Dennis J. Sweeney | Thomas A. Williams | Jeffrey D. Camm | James J. Cochran
Essentials of Statistics for Business and Economics 8th Edition
David R. Anderson | Dennis J. Sweeney | Thomas A. Williams | Jeffrey D. Camm | James J. Cochran
ISBN-13: 9781337114172 | ISBN-10: 1337114170
© 2018 | Published |  NA  Pages
Previous Editions: 2015

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Hard/Casebound Book or Journal
US $249.95
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Introduce sound statistical methodology to students with the real-world examples, proven approach, and hands-on exercises in ESSENTIALS OF STATISTICS FOR BUSINESS AND ECONOMICS, 8E. This leading book builds the foundation for to analyze and solve business problems quantitatively. The authors’ signature problem-scenario approach and reader-friendly writing in this streamlined edition focuses on core topics with updated case problems, applications, and self-tests help students master key formulas and apply statistical methods to business scenarios.

MindTap® and CengageNOW™ complete digital solutions help you and your students make the most of the course. Online homework now includes "Post-Submission Feedback" or step-by-step calculations that walk through solutions. Optional chapter appendices deliver in-depth coverage of a popular statistical software program that can be integrated with the text. Choose from Excel® 2016 with add-in XLSTAT or Minitab® 17.

  • 1. Data and Statistics.
    2. Descriptive Statistics: Tabular and Graphical Displays.
    3. Descriptive Statistics: Numerical Measures.
    4. Introduction to Probability.
    5. Discrete Probability Distributions.
    6. Continuous Probability Distributions.
    7. Sampling and Sampling Distributions.
    8. Interval Estimation.
    9. Hypothesis Tests.
    10. Inference about Means and Proportions with Two Populations.
    11. Inferences about Population Variances.
    12. Comparing Multiple Proportions, Test of Independence and Goodness of Fit.
    13. Experimental Design and Analysis of Variance.
    14. Simple Linear Regression.
    15. Multiple Regression.
    Appendix A: References and Bibliography.
    Appendix B: Tables.
    Appendix C: Summation Notation.
    Appendix D: Self-Test Solutions and Answers to Even-Numbered Exercises. (online)
    Appendix E: Microsoft Excel 2016 and Tools for Statistical Analysis.
    Appendix F: Computing p-Values Using Minitab and Excel.

    • CENGAGENOW™ ONLINE COURSE MANAGEMENT SYSTEM ALLOWS YOU TO PERSONALIZE INSTRUCTION IN LESS TIME. This online tool helps you plan your course, manage and automatically grade assignments, prepare and teach lessons, create tests, and provide personalized study plans for each student. A Solutions Manual written by the text's authors and reviewed by subject matter experts provides step-by-step solutions for exercises, including detailed explanations of the role of cumulative normal distribution and p-values, to help make lecture preparation effortless.
    • MODERN, COMPREHENSIVE SOFTWARE IS INTEGRATED THROUGHOUT. Optional chapter appendices are now updated and expanded to address both Excel® 2016 and Minitab® 17. This coverage gives your students hands-on experience working with the current versions of two of the most commonly used software for statistical analysis in business.
    • HELPFUL APPENDICES DETAIL HOW TO USE TOOLS WITHIN EXCELA primer appendix introduces Microsoft® Excel® 2016 and its tools for statistical analysis. Students learn to how to use the Ribbon, basic workbook operations, and functions for statistical analysis.
    • COVERAGE INTEGRATES IMPORTANT BUSINESS ANALYTICS TOPICS. This edition addresses key business material that is not covered in any other single book, including data mining, data visualization, analytics and data dashboards.
    • STEP-BY-STEP INSTRUCTIONS GUIDE STUDENTS THROUGH USING THE LATEST SOFTWARE TOOLS. Students master the skills how to use various software to perform the analyses discussed in the book as they work with Excel® 2016 and Minitab® 17.
    • COMPREHENSIVE, MODERN COVERAGE ADDRESSES THE LATEST DEVELOPMENTS IN THE FIELD. Demonstrating the myriad uses of statistics in business and economics, this edition’s examples and exercises incorporate the most current data, recent studies, and reliable sources of statistical information available, such as the Wall Street Journal, USA Today, Barron's, and others.
    • UNIQUE PROBLEM-SCENARIO APPROACH ENSURES STUDENT COMPREHENSION. Students discuss and develop their understanding of each statistical concept by applying techniques to exercises designed to generate a solution or recommendation and illustrate the value of statistics in business decision-making.
    • REAL-WORLD PROBLEMS AND APPLICATIONS KEEP STUDENTS ENGAGED AND ACTIVELY LEARNING. Methods, applications, and self-test exercises allow students to develop analytical skills by using formulas, making computations, and applying chapter material to realistic situations. Students evaluate their understanding of key concepts against solutions to exercises in a special appendix.
    • EXPANDED COVERAGE ADDRESSES HOT TOPICS, INCLUDING DATA MINING AND BIG DATA. Several new sections now cover the topic of analytics. The authors also place greater emphasis on the distinction between observed and experimental data in this edition.
    • MINDTAP COMPLETE DIGITAL SOLUTION NOW FEATURES ALL-NEW EXCEL ONLINE INTEGRATION. Students working with MINDTAP can now use Excel, powered by Microsoft®, for completing work in your business statistics course. These enhancements take students from learning basic statistical concepts to actively engaging in critical-thinking applications, while mastering valuable hands-on skills for future careers.
For more information about these supplements, or to obtain them, contact your Learning Consultant

  • Dr. David R. Anderson is a textbook author and Professor Emeritus of Quantitative Analysis in the College of Business Administration at the University of Cincinnati. He has served as head of the Department of Quantitative Analysis and Operations Management and as Associate Dean of the College of Business Administration. He was also coordinator of the College’s first Executive Program. In addition to introductory statistics for business students, Dr. Anderson has taught graduate-level courses in regression analysis, multivariate analysis, and management science. He also has taught statistical courses at the Department of Labor in Washington, D.C. Professor Anderson has received numerous honors for excellence in teaching and service to student organizations. He is the coauthor of ten textbooks related to decision sciences and actively consults with businesses in the areas of sampling and statistical methods. Born in Grand Forks, North Dakota, he earned his BS, MS, and PhD degrees from Purdue University.

    Dr. Dennis J. Sweeney is a leading textbook author, Professor Emeritus of Quantitative Analysis, and founder of the Center for Productivity Improvement at the University of Cincinnati. He also served five years as head of the Department of Quantitative Analysis and four years as Associate Dean of the College of Business Administration. In addition, Dr. Sweeney has worked in the management science group at Procter & Gamble and has been a visiting professor at Duke University. Dr. Sweeney has published more than 30 articles in the area of management science and statistics. The National Science Foundation, IBM, Procter & Gamble, Federated Department Stores, Kroger, and Cincinnati Gas & Electric have funded his research, which has been published in Management Science, Operations Research, Mathematical Programming, Decision Sciences, and other respected journals. Dr. Sweeney is the co-author of ten textbooks in the areas of statistics, management science, linear programming, and production and operations management. Born in Des Moines, Iowa, he earned a B.S. degree from Drake University, graduating summa cum laude. He received his M.B.A. and D.B.A. degrees from Indiana University, where he was an NDEA Fellow.

    Dr. Thomas A. Williams is a well respected textbook author and Professor Emeritus of Management Science in the College of Business at Rochester Institute of Technology, where he was the first chairman of the Decision Sciences Department. He taught courses in management science and statistics, as well as graduate courses in regression and decision analysis. Before joining the College of Business at RIT, Dr. Williams served for seven years as a faculty member in the College of Business Administration at the University of Cincinnati, where he developed the undergraduate program in Information Systems and served as its coordinator. The co-author of 11 leading textbooks in the areas of management science, statistics, production and operations management, and mathematics, Dr. Williams has been a consultant for numerous Fortune 500 companies and has worked on projects ranging from the use of data analysis to the development of large-scale regression models. He earned his B.S. degree at Clarkson University and completed his graduate work at Rensselaer Polytechnic Institute, where he received his M.S. and Ph.D. degrees.

    Jeffrey D. Camm is the Inmar Presidential Chair and Associate Dean of Analytics in the School of Business at Wake Forest University. Born in Cincinnati, Ohio, he holds a B.S. from Xavier University in Ohio, and a Ph.D. from Clemson University. Prior to joining the faculty at Wake Forest, he served on the faculty of the University of Cincinnati. He has also been a visiting scholar at Stanford University and a visiting professor of business administration at the Tuck School of Business at Dartmouth College. Dr. Camm has published more than 30 papers in the general area of optimization applied to problems in operations management and marketing. He has published his research in Science, Management Science, Operations Research, Interfaces, and other professional journals. Dr. Camm was named the Dornoff Fellow of Teaching Excellence at the University of Cincinnati and he was the 2006 recipient of the INFORMS Prize for the Teaching of Operations Research Practice. A firm believer in practicing what he preaches, he has served as an operations research consultant to numerous companies and government agencies. From 2005 to 2010 he served as editor-in-chief of Interfaces and has also served on the editorial board of INFORMS Transactions on Education.

    James J. Cochran is Professor of Applied Statistics and the Rogers-Spivey Faculty Fellow at the University of Alabama. Born in Dayton, Ohio, he earned
    his B.S., M.S., and M.B.A. degrees from Wright State University and a Ph.D. from the
    University of Cincinnati. He has been at the University of Alabama since 2014 and has
    been a visiting scholar at Stanford University, Universidad de Talca, the University of
    South Africa and Pole Universitaire Leonard de Vinci.