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Modern Business Statistics with Microsoft® Excel®,
7th Edition

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

ISBN-13: 9780357131381 | ISBN-10: 035713138x

Copyright 2021

| Published 2020

| 1008 pages

List Price USD $249.95

Overview

Develop a strong conceptual understanding of statistics and its importance in business today. MODERN BUSINESS STATISTICS WITH MICROSOFT® EXCEL®, 7E balances real-world applications with an integrated focus on the latest version of Microsoft® Excel®. This best-selling, comprehensive edition clearly develops each statistical technique in an application setting. You master statistical methodology with an easy-to-follow presentation of a statistical procedure followed by a discussion of how to use Excel® to perform the procedure. Step-by-step instructions and screen images reinforce understanding. More than 160 new business examples, proven methods, and application exercises show how statistics provide insights into business decisions and problems. A problem-scenario approach emphasizes how to apply statistical methods to practical business situations. New case problems let you check your understanding, while MindTap digital resources help you master Excel®, Excel Online, and R.

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Meet the Authors

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Dr. David R. Anderson is a leading 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. Dr. Anderson has received numerous honors for excellence in teaching and service to student organizations. He is the co-author of ten well-respected 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 B.S., M.S., and Ph.D. degrees from Purdue University.

Dennis J. Sweeney is Professor Emeritus of Quantitative Analysis and founder of the Center for Productivity Improvement at the University of Cincinnati. Born in Des Moines, Iowa, he earned a BSBA degree from Drake University and his MBA and DBA degrees from Indiana University, where he was an NDEA Fellow. Professor Sweeney has worked in the management science group at Procter & Gamble and has been a visiting professor at Duke University. Professor Sweeney served as Head of the Department of Quantitative Analysis and four years as Associate Dean of the College of Business Administration at the University of Cincinnati. Professor Sweeney has published more than 30 articles and monographs 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 journals. Professor Sweeney has co-authored ten textbooks in the areas of statistics, management science, linear programming and production and operations management.

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Dr. Jeffrey D. Camm is the Inmar Presidential Chair and Associate Dean of Business Analytics in the School of Business at Wake Forest University. Born in Cincinnati, Ohio, he holds a B.S. from Xavier University (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 served as a visiting scholar at Stanford University and as a visiting Professor of Business Administration at the Tuck School of Business at Dartmouth College. Dr. Camm has published more than 40 papers in the general area of optimization applied to problems in operations management and marketing. He has published his research in numerous professional journals, including Science, Management Science, Operations Research and Interfaces. 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. In 2016, Dr. Camm received the George E. Kimball Medal for service to the operations research profession and in 2017 he was named an INFORMS Fellow.

James J. Cochran is Associate Dean for Research, 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. from Wright State University and his 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. Dr. Cochran has published more than 40 papers in the development and application of operations research and statistical methods. He has published in several journals, including Management Science, The American Statistician, Communications in Statistics—Theory and Methods, Annals of Operations Research, European Journal of Operational Research, Journal of Combinatorial Optimization, Interfaces and Statistics and Probability Letters. He received the 2008 INFORMS Prize for the Teaching of Operations Research Practice, 2010 Mu Sigma Rho Statistical Education Award and 2016 Waller Distinguished Teaching Career Award from the American Statistical Association. Dr. Cochran was elected to the International Statistics Institute in 2005, was named a Fellow of the American Statistical Association in 2011 and was named a Fellow of INFORMS in 2017. He received the Founders Award in 2014, the Karl E. Peace Award in 2015 from the American Statistical Association and the INFORMS President’s Award in 2019. A strong advocate for effective operations research and statistics education as a means of improving the quality of applications to real problems, Dr. Cochran has chaired teaching effectiveness workshops around the globe. He has served as operations research consultant to numerous companies and not-for-profit organizations.

Michael J. Fry is Professor of Operations, Business Analytics, and Information Systems (OBAIS) and Academic Director of the Center for Business Analytics in the Carl H. Lindner College of Business at the University of Cincinnati. Born in Killeen, Texas, he earned a B.S. from Texas A&M University, and M.S.E. and Ph.D. degrees from the University of Michigan. He has been at the University of Cincinnati since 2002, where he was previously department chair and has been named a Lindner Research Fellow. He has also been a visiting professor at the Samuel Curtis Johnson Graduate School of Management at Cornell University and the Sauder School of Business at the University of British Columbia. Dr. Fry has published more than 25 research papers in journals such as Operations Research, M&SOM, Transportation Science, Naval Research Logistics, IIE Transactions, Critical Care Medicine and Interfaces. His research interests focus on applying analytics to the areas of supply chain management, sports and public-policy operations. He has worked with many different organizations for his research, including Dell, Inc., Starbucks Coffee Company, Great American Insurance Group, the Cincinnati Fire Department, the State of Ohio Election Commission, the Cincinnati Bengals and the Cincinnati Zoo & Botanical Garden. He was named a finalist for the Daniel H. Wagner Prize for Excellence in Operations Research Practice, and he has been recognized for both his research and teaching excellence at the University of Cincinnati. In 2019 he led the team that was awarded the INFORMS UPS George D. Smith Prize on behalf of the OBAIS Department at the University of Cincinnati.

Jeffrey W. Ohlmann is Associate Professor of Business Analytics and Huneke Research Fellow in the Tippie College of Business at the University of Iowa. Born in Valentine, Nebraska, he earned a B.S. from the University of Nebraska, and M.S. and Ph.D. degrees from the University of Michigan. He has taught at the University of Iowa since 2003. Dr. Ohlmann’s research on the modeling and solution of decision-making problems has produced more than two dozen research papers in journals, such as Operations Research, Mathematics of Operations Research, INFORMS Journal on Computing, Transportation Science and European Journal of Operational Research. He has collaborated with companies such as Transfreight, LeanCor, Cargill and the Hamilton County Board of Elections as well as three National Football League franchises. Because of the relevance of his work to the industry, he was bestowed the George B. Dantzig Dissertation Award and was recognized as a finalist for the Daniel H. Wagner Prize for Excellence in Operations Research Practice.

  • NEW AND UPDATED CASE PROBLEMS ENCOURAGE STUDENTS TO APPLY SKILLS. This edition adds four new case problems for a total of 47 relevant, timely cases. An updated case on graphical display appears in Chapter 2, and an updated case on descriptive statistics appears in Chapter 3. A new case on nonparametric procedures is now added to Chapter 18 with a new case on sample survey methods added to Chapter 21. The numerous case problems in this edition enable students to work on more complex problems, analyze larger data sets, and prepare managerial reports based on the results of their analyses.
  • NEW COVERAGE INTRODUCES THE LATEST STATISTICAL SOFTWARE TOOLS. This edition's proven step-by-step instructions and screen images demonstrate how to use the latest version of Excel 2019 to implement statistical procedures. Clear instructions in MindTap Reader also guide students in using Excel Online and R for statistical computing and graphics.
  • NEW EXAMPLES AND EXERCISES INCORPORATE THE LATEST REAL DATA. More than 160 new examples and exercises are part of this edition's 980 examples and exercises drawn from the today's most current real data and referenced sources of statistical information. The authors use data from The Wall Street Journal, USA Today, The Financial Times, and Forbes as well as from actual studies and applications to create explanations and exercises that demonstrate the use of statistics in business and economics with interest, relevant problems. All applications now clearly identify the skills each exercise reinforces.
  • POWERFUL EXAMPLES AND EXERCISES MAKE CONCEPTS REAL AND MEMORABLE FOR STUDENTS. This acclaimed author team is known for creating exceptional exercises and examples that are strengthened with real data from sources such as the Census Bureau and The Wall Street Journal. Exercises drawn from real events encourage students to learn the statistical methodology and apply real data to problems. Approximately 160 new or updated examples and exercises now add to this edition's more than 980 exercises.
  • MINDTAP COMPLETE DIGITAL SOLUTION FEATURES EXCEL ONLINE INTEGRATION POWERED BY MICROSOFT®. Ideal for your business statistics course, MindTap takes students from learning basic statistical concepts to actively engaging in critical thinking applications, while learning valuable software skills for future careers. MindTap customizable course solution includes an interactive eBook and auto-graded, algorithmic exercises from the latest edition of the printed text. Students can easily access the latest statistical principles in application settings that enable them to truly master the materials.
  • TRUSTED TEAM OF EXPERT AUTHORS ENSURE QUALITY, PRACTICALLY FOCUSED PRESENTATION. As respected leaders and active consultants in the fields of business and statistics, this acclaimed team of authors -- Anderson, Sweeney, Williams, Camm, Cochran, Fry, and Ohlmann -- provide an accurate presentation of statistical concepts with every edition. They use their teaching experience to provide a cohesive, student-friendly writing approach. To ensure accuracy, the authors personally triple-check all problems and examples.
  • PROVEN EXERCISES ENSURE STUDENT UNDERSTANDING: Completely worked-out solutions for specific exercises appear in an appendix at the end of this edition. Students can complete the exercises and immediately check their solutions to evaluate their understanding of the concepts presented in each chapter.
  • THIS EDITION PROVIDES BALANCED EMPHASIS ON METHODS AND APPLICATIONS. This experienced author team strikes an appropriate balance in methodology and application. Methods Exercises at the end of each section require students to use formulas and make necessary computations, while practical Application Exercises ask students to apply the chapter material to address real-world problems.
  • "STATISTICS IN PRACTICE" CHAPTER OPENERS IMMEDIATELY EMPHASIZE THE PRACTICAL VALUE OF INFORMATION STUDENTS ARE LEARNING. "Statistics in Practice" chapter openers highlight intriguing scenarios from companies such as Citibank and Procter & Gamble and clearly demonstrate the value of statistics in everyday business situations. These high-interest openers immediately draw students into the chapter information that follows.

Table of Contents

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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. Statistical Inferences 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. Decision Analysis (online).
21. Sample Survey (online).
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.

Cengage provides a range of supplements that are updated in coordination with the main title selection. For more information about these supplements, contact your Learning Consultant.

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Modern Business Statistics with Microsoft® Excel®

  • ISBN-10: 035713138x
  • ISBN-13: 9780357131381

Price USD$ 249.95

eBook: Modern Business Statistics with Microsoft® Excel® 12Months

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