Modern Business Statistics with Microsoft® Office Excel®, Loose-Leaf Version 6th Edition
David R. Anderson | Dennis J. Sweeney | Thomas A. Williams | Jeffrey D. Camm | James J. Cochran
Modern Business Statistics with Microsoft® Excel® 5th Edition
David R. Anderson | Dennis J. Sweeney | Thomas A. Williams
ISBN-13: 9781305082182 | ISBN-10: 1305082184
© 2015 | Published |  1056  Pages

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Give students a balanced, conceptual understanding of statistics with a focus on real-world applications and the integrated strengths of Microsoft® Excel® 2013. The authoritative leader in modern business statistics, this best-selling, comprehensive text carefully discusses and clearly develops each statistical technique in an application setting.

Microsoft® Excel® 2013 instruction, which is integrated in each chapter, plays an integral part in strengthening this edition's applications orientation. Immediately after each easy-to-follow presentation of a statistical procedure, a subsection discusses how to use Excel® to perform the procedure. This integrated approach emphasizes the applications of Excel® while focusing on the statistical methodology. Step-by-step instructions and screen captures further clarify student learning.

A wealth of timely business examples, proven methods, and additional exercises throughout this edition demonstrate how statistical results provide insights into business decisions and present solutions to contemporary business problems. High-quality problems noted for their unwavering accuracy and the authors' signature problem-scenario approach clearly show how to apply statistical methods to practical business situations. New case problems and self-tests allow students to challenge their personal understanding. This edition's comprehensive support package, including the CengageNOW course management system, provides everything you and your students need for an understanding of business statistics. Anderson/Sweeney/Williams' MODERN BUSINESS STATISTICS, 5e, is simply excellent!



  • 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 on Website.
    21. 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 2013 and Tools for Statistical Analysis.

    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 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, he has worked in the management science group at Procter & Gamble and has been a visiting professor at Duke University. Professor 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 journals. Dr. Sweeney is the coauthor 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 BS degree from Drake University, graduating summa cum laude. He received his MBA and DBA degrees from Indiana University, where he was an NDEA Fellow.

      Dr. Thomas A. Williams is Professor 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 teaches courses in management science and statistics, as well as graduate courses in regression and decision analysis. Before joining the College of Business at RIT, Professor 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 then served as its coordinator. The co-author of 11 leading textbooks in the areas of management science, statistics, production and operations management, and mathematics, Professor 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.