Mindtap Business Statistics, 1 Term (6 Months) Printed Access Card for Anderson/Sweeney/Williams' Essentials of Modern Business Statistics with Microsoft Office Excel, 7th

Author:   David R Anderson ,  Dennis J Sweeney ,  Thomas A Williams
Publisher:   Cengage Learning
Edition:   7th ed.
ISBN:  

9781337390613


Publication Date:   11 April 2017
Format:   Online resource
Availability:   Available To Order   Availability explained
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Mindtap Business Statistics, 1 Term (6 Months) Printed Access Card for Anderson/Sweeney/Williams' Essentials of Modern Business Statistics with Microsoft Office Excel, 7th


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MindTap PROVIDES YOU WITH THE TOOLS YOU NEED TO BETTER MANAGE YOUR LIMITED TIME. --With MindTap you can complete assignments whenever and wherever you are ready to learn with course material specially customized for you by your instructor and streamlined in one proven, easy-to-use interface. MindTap gives you a roadmap to master decision-making in business statistics. With an array of resources, tools, and apps --- including all new Excel Online activities powered by Microsoft, new Exploring Statistics interactive visualizations, problem-solving videos, animated examples and practice opportunities, decision simulations Interpreting the Results assignments, note taking, and flashcards -- you'll get a true understanding of course concepts, helping you to achieve better grades and setting the groundwork for your future courses.

Full Product Details

Author:   David R Anderson ,  Dennis J Sweeney ,  Thomas A Williams
Publisher:   Cengage Learning
Imprint:   Cengage Learning
Edition:   7th ed.
Weight:   0.020kg
ISBN:  

9781337390613


ISBN 10:   1337390615
Publication Date:   11 April 2017
Audience:   General/trade ,  General
Format:   Online resource
Publisher's Status:   Active
Availability:   Available To Order   Availability explained
We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately.

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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. N/A

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