Modern Business Statistics with Microsoft® Excel® 5th Edition
David R. Anderson | Dennis J. Sweeney | Thomas A. Williams
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Modern Business Statistics with Microsoft® Office Excel® (with XLSTAT Education Edition Printed Access Card) 6th Edition
David R. Anderson | Dennis J. Sweeney | Thomas A. Williams | Jeffrey D. Camm | James J. Cochran
ISBN-13: 9781337115186 | ISBN-10: 1337115185
© 2018 | Published |  NA  Pages
Previous Editions: 2015

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Hardback
US $249.95
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Provide a balanced, conceptual understanding of statistics as MODERN BUSINESS STATISTICS, 6E focuses on real applications and Microsoft® Excel® 2016. This best-selling, comprehensive leader develops each statistical technique in an application setting with integrated Microsoft® Excel® 2016 instruction. Content focuses on statistical methodology as each presentation of a statistical procedure is followed by a discussion of how to use Excel® to perform the procedure. Step-by-step instructions and screen captures ensure understanding.

Business examples and application exercises demonstrate how statistical results provide insights into business decisions and problems. High-quality problems, noted for unwavering accuracy, and a signature problem-scenario approach apply statistical methods to business situations. New case problems and self-tests check reader understanding, while comprehensive support with MindTap® and CengageNOW™ reinforce an understanding of business statistics.



  • 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.

    • MINDTAP® COMPLETE DIGITAL SOLUTION NOW FEATURES ALL-NEW 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 their future careers. MindTap® is a customizable digital course solution that includes an interactive eBook and auto-graded, algorithmic exercises from the textbook. All of these materials offer students better access that enable them to truly master the materials in your course.
    • CENGAGENOW™ FULLY INTEGRATED ONLINE TEACHING AND LEARNING SYSTEM SAVES TIME WHILE ENSURING STUDENT MASTERY. This innovative course management system combines the best of current technology to help you plan your course, manage and automatically grade extensive homework and student assignments. You teach with the latest built-in technology support and test students using a customized test bank. Personalized study plans for each student help reinforce student comprehension and reduce questions.
    • POWERFUL EXAMPLES AND EXERCISES MAKE CONCEPTS REAL AND MEMORABLE FOR STUDENTS. A well-known strength of this author team, exceptional exercises and examples throughout this edition are strengthened with more 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 140 new examples and exercises have been added to the book's more than 980 exercises.
    • PROVEN SELF-TEST EXERCISES ENSURE STUDENT UNDERSTANDING: Completely worked-out solutions for specific exercises appear in an appendix at the end of the book. Students can complete the self-test exercises and immediately check their solutions to evaluate their understanding of the concepts presented in the chapter.
    • STATISTICS IN PRACTICE CHAPTER OPENERS IMMEDIATELY EMPHASIZE THE PRACTICAL VALUE OF THE 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 draw students into the chapter information that follows.
    • AUTHORS EQUALLY EMPHASIZE METHODS AND APPLICATIONS. This experienced author team strikes an appropriate balance as Methods Exercises at the end of each section require students to use formulas and make necessary computations. In addition, practical Application Exercises ask students to apply the chapter material to address real-world problems.
    • TRUSTED TEAM OF EXPERT AUTHORS ENSURE A QUALITY, PRACTICALLY FOCUSED PRESENTATION. As respected leaders and active consultants in the fields of business and statistics, Anderson, Sweeney, Williams, Camm and Cochran provide an accurate presentation of statistical concepts you can trust with every edition. They use their teaching experience to provide a cohesive, student-friendly writing approach. To ensure accuracy, the authors triple-check all problems and examples themselves.
    • INTEGRATED MICROSOFT® EXCEL® 2016 FEATURES STEP-BY-STEP INSTRUCTIONS AND SCREEN CAPTURES. These visuals and instructions clearly demonstrate how to use the latest version of Excel® to implement statistical procedures. Students learn how Excel's new recommended PivotTables tool and new Recommended Chart tool are extremely useful in developing tabular and graphical displays.
    • NEW EXCEL® 2016 PRIMER ADDRESSES BASIC OPERATIONS FOR STUDENTS WHO NEED REVIEW OR ADDITIONAL INSTRUCTION. This new section of material -- "Microsoft Excel 2016 Tools for Statistical Analysis" -- appears as an appendix at the end of the book. Content emphasizes basic Excel® operations and discusses how to open and save workbooks, copy and paste, and enter formulas.
    • REVISED CONTENT IN CHAPTER 1 CLEARLY INTRODUCES ANALYTICS. A new section on analytics describes what analytics is, the types of analytics used in business today and how this relates to statistics. An expanded section on data mining in this initial chapter includes a discussion of big data and how businesses use data mining for competitive advantage.
    • REVISED, CLEAR COVERAGE EMPHASIZES HOW TO USE BOXPLOTS WITHIN EXCEL 2016. Chapter 3 offers new, additional coverage that details how to use Excel 2016 to create boxplots and comparative boxplots.
    • NEW SECTION HIGHLIGHTS THE PRACTICAL IMPLICATIONS OF BIG DATA ON SAMPLING ERROR. This new content in Chapter 7 now discusses big data in detail.
    • ADDITIONAL CONTENT NOW EMPHASIZES THE PRACTICAL IMPLICATIONS OF BIG DATA ON CONFIDENCE INTERVALS. New insights and coverage in this edition's revised Chapter 8 highlight how today's big data impacts confidence intervals.
    • NEW CONTENT NOW DETAILS THE PRACTICAL IMPLICATIONS OF BIG DATA ON HYPOTHESIS TESTING. The authors have added coverage within this edition's revised Chapter 9 that emphasizes how use of big data can impact hypothesis testing.
    • NEW, ADDITIONAL CASE PROBLEMS PROVIDE MORE PRACTICE ANALYZING AND PREPARING REPORTS. This edition includes 11 new case problems to challenge your students. The 30 case problems in the text provide students with the opportunity to analyze somewhat larger data sets and to prepare managerial reports based on the results of their analyses.
    • UPDATED AND IMPROVED END-OF-CHAPTER SOLUTIONS AND SOLUTIONS MANUAL ENSURE ACCURATE, TRUSTED ANSWERS. The authors have carefully reviewed and reworked, when needed, every question and solution in this edition's end-of chapter solutions and solutions manual. The solutions now boast higher accuracy and contain additional details to assist in efficient grading. You'll find improved rounding instructions, expanded explanations with a student-focus, and alternative answers using Excel and a statistical calculator.
For more information about these supplements, or to obtain them, contact your Learning Consultant

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  • 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.