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New

Statistics for Business & Economics, Revised 13th Edition

David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Jeffrey D. Camm, James J. Cochran

  • Published
  • Previous Editions 2017
Starting At 135.00 See pricing and ISBN options

Overview

Clearly demonstrate how statistical information enables strong decisions in today’s business world with STATISTICS FOR BUSINESS AND ECONOMICS, REVISED 13E. Sound methodology combines with a proven problem-scenario approach, and meaningful applications for the most powerful approach to teaching business statistics available. Prestigious authors bring more than 25 years of unmatched experience to this thoroughly updated text. More than 350 real business examples, cases, and memorable exercises present the latest statistical data and business information with unwavering accuracy. You select the topics to give you the most relevant text for your course, including coverage of popular commercial statistical software, such as Minitab 17 and Excel 2016. Excel add-in XLSTAT is also available. Optional chapter appendices, coordinating online data sets, and support materials, such as the CengageNOW™ online course management system, make this edition customizable and efficient.

David R. Anderson, University of Cincinnati

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.

Dennis J. Sweeney, University of Cincinnati

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.

Thomas A. Williams, Rochester Institute of Technology

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, Wake Forest University

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, University of Alabama

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.
  • TRUSTED TEAM OF EXPERT AUTHORS ENSURES THE MOST ACCURATE, PROVEN PRESENTATION. As prominent, respected leaders and active consultants in business and statistics today, authors David R. Anderson, Dennis J. Sweeney, and Thomas A. Williams, Jeffrey D. Camm, and James J. Cochran provide an accurate timely presentation of statistical concepts you and your students can trust with every edition.
  • LEADING PROBLEM-SCENARIO APPROACH HELPS STUDENT UNDERSTAND AND APPLY CONCEPTS. A hallmark strength of this text, this unique problem-scenario approach guides students in understanding statistical techniques within an applications setting. The statistical results provide insights into business decisions and detail how professionals regularly use statistics in business to solve problems.
  • SYSTEMATIC APPROACH EMPHASIZES PROVEN METHODS AND APPLICATIONS. Students first develop a computational foundation and learn to use techniques before moving to statistical application and interpretation of the value of techniques. Methods Exercises at the end of each section stress computation and the use of formulas, while Application Exercises require students to use what they know about statistics to address real-world problems.
  • CENGAGENOW™ ONLINE COURSE MANAGEMENT SYSTEM PROVIDES STUDENT RESULTS NOW. This robust, online course management system gives you more control in less time and delivers better student outcomes. Teaching and learning resources are organized around lectures and enable you to create assignments and quizzes and track student progress and performance easily. Flexible assignments, automatic grading and a gradebook option provide more control while saving you valuable time. A Personalized Study diagnostic tool empowers students to master concepts, prepare for exams, and become more involved in class.
  • USE OF CUMULATIVE STANDARD NORMAL DISTRIBUTION TABLE PREPARES STUDENTS TO WORK WITH STATISTICAL SOFTWARE. To more effectively prepare today's students to use computer software in statistics, this book incorporates a normal probability table that is consistent with today's most popular statistical software. This cumulative normal probability table also makes it easier to compute p-values for hypothesis testing.
  • COVERAGE HIGHLIGHTS DATA MINING, BIG DATA AND ANALYTICS. A proven section on analytics describes what analytics is, the types of analytics used in business and how this relates to statistics. An expanded section on data mining includes a discussion of big data and how businesses today are using data mining to establish competitive advantages.
Preface.
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.
16. Regression Analysis: Model Building.
17. Time Series Analysis and Forecasting.
18. Nonparametric Methods.
19. Statistical Methods for Quality Control.
20. Index Numbers.
21. Decision Analysis (On Website).
22. Sample Survey (On Website).
Appendix A: References and Bibliography.
Appendix B: Tables.
Appendix C: Summation Notation.
Appendix D: Self-Test Solutions and Answers to Even –Numbered Exercises.
Appendix E: Microsoft Excel 2016 and Tools for Statistical Analysis.
Appendix F: Computing p-Values Using Minitab and Excel.
Index.
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This Cengage solution can be seamlessly integrated into most Learning Management Systems (Blackboard, Brightspace by D2L, Canvas, Moodle, and more) but does require a different ISBN for access codes. Please work with your Cengage Learning Consultant to ensure the proper course set up and ordering information. For additional information, please visit the LMS Integration site.

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This Cengage solution can be seamlessly integrated into most Learning Management Systems (Blackboard, Brightspace by D2L, Canvas, Moodle, and more) but does require a different ISBN for access codes. Please work with your Cengage Learning Consultant to ensure the proper course set up and ordering information. For additional information, please visit the LMS Integration site.

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