Contemporary Business Statistics, International Edition (with Printed Access Card)

Mixed media product

Main Details

Title Contemporary Business Statistics, International Edition (with Printed Access Card)
Authors and Contributors      By (author) David Anderson
By (author) Thomas Arthur Williams
By (author) Dennis Sweeney
Physical Properties
Format:Mixed media product
Pages:1088
Dimensions(mm): Height 254,Width 204
Category/GenreBusiness mathematics and systems
Probability and statistics
ISBN/Barcode 9781111534219
ClassificationsDewey:519.502465
Audience
Tertiary Education (US: College)
Edition 4th edition

Publishing Details

Publisher Cengage Learning, Inc
Imprint South-Western College Publishing
Publication Date 11 May 2011
Publication Country United States

Description

Use CONTEMPORARY BUSINESS STATISTICS, 4e, International Edition to gain a strong conceptual understanding of statistics with a balance of real-world applications and focus on the integrated strengths of Microsoft (R) Excel (R) 2010. To ensure your understanding, this best-selling, comprehensive text carefully discusses and clearly develops each statistical technique in a solid application setting. Immediately after each easy-to-follow presentation of a statistical procedure, a subsection discusses how to use Excel (R) to perform the procedure. This integrated approach emphasizes the applications of Excel (R) while maintaining a focus on the statistical methodology. Step-by-step instructions and screen captures further clarify the presentation to ensure your understanding. A wealth of timely business examples, proven methods, and application exercises clearly demonstrate how statistical results provide insights into business decisions and present solutions to contemporary business problems. The book's class-tested problem-scenario approach emphasizes how you can apply statistical methods to today's practical business situations. New case problems and self-tests throughout this edition allow you to check your personal understanding. Additional learning resources, including CengageNOW for online homework assistance and a complete support Website, provide everything you need for the Excel (R) 2010 skills and understanding of business statistics that is SIMPLY EXCELLENT!

Author Biography

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.

Reviews

1. Data and Statistics. 2. Descriptive Statistics: Tabular and Graphical Presentations. 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. Inferences About Means and Proportions with Two Populations. 11. Inferences About Population Variances. 12. Tests of Goodness of Fit and Independence. 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. 21. Sample Survey On Website.