Statistics for Business and Economics, Revised (with Printed Access Card) / Edition 11

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Overview

The revised, eleventh edition of STATISTICS FOR BUSINESS AND ECONOMICS brings together more than twenty-five years of author experience, sound statistical methodology, a proven problem-scenario approach, and meaningful applications to demonstrate how statistical information informs decisions in the business world. And, to give you the most relevant material, you select the topics you want, including coverage of popular commercial statistical software programs like Minitab 16, Excel 2010, and others. These optional chapter appendices, coordinating data sets (on CD and online), and other support materials make STATISTICS FOR BUSINESS AND ECONOMICS the most customizable, efficient, and powerful approach to learning business statistics around.

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Product Details

  • ISBN-13: 9780538481649
  • Publisher: Cengage Learning
  • Publication date: 3/30/2011
  • Edition description: Revised
  • Edition number: 11
  • Pages: 1064
  • Sales rank: 602,998
  • Product dimensions: 8.30 (w) x 10.30 (h) x 1.70 (d)

Meet the Author

Dr. David R. Anderson is Professor Emeritus of Quantitative Analysis in the College of Business Administration at the University of Cincinnati. He earned his B.S., M.S., and Ph.D. degrees from Purdue University. Professor Anderson has served as Head of the Department of Quantitative Analysis and Operations Management and as Associate Dean of the College of Business Administration. In addition, he was the coordinator of the College's first Executive Program. At the University of Cincinnati, Professor Anderson has taught introductory statistics for business students as well as graduate-level courses in regression analysis, multivariate analysis, and management science. He has also taught statistical courses at the Department of Labor in Washington, D.C. He has been honored with numerous nominations and awards for excellence in teaching and excellence in service to student organizations. Professor Anderson has co-authored 10 leading textbooks in the areas of statistics, management science, linear programming, and production and operations management. He is an active consultant in the field of sampling and statistical methods.

Dr. Dennis J. Sweeney is Professor Emeritus of Quantitative Analysis and Founder of the Center for Productivity Improvement at the University of Cincinnati. 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 served as visiting professor at Duke University. Professor Sweeney also has served as Head of the Department of Quantitative Analysis and 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 coauthored ten leading texts in the areas of statistics, management science, linear programming, and production and operations management.

Dr. Thomas A. Williams is Professor Emeritus of Management Science in the College of Business at Rochester Institute of Technology (RIT). He earned his BS degree at Clarkson University. He completed his graduate work at Rensselaer Polytechnic Institute, where he received his MS and PhD degrees. 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. At RIT, 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. Professor Williams is the coauthor of 11 leading textbooks in the areas of management science, statistics, production and operations management, and mathematics. He 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.

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Table of Contents

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. Inference 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. Index Numbers. 18. Time Series Analysis and Forecasting. 19. Nonparametric Methods. 20. Statistical Methods for Quality Control. 21. Decision Analysis. 22. Sample Survey (Online only). 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 2010 Tools for Statistical Analysis. Appendix F: Computing p-Values Using Minitab and Excel.

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