2008 Hardcover Fair NO CD; No Access Code; Some highlighting, markings, tears, scratches, creases, discoloration and wrinkling; Significant edge, cover and corner wear; Unless ...stated otherwise herein the notes, complementary books or items are not present; $20.00 minimum excluding shipping for orders to Puerto Rico & Hawaii; standard shipping is by USPS Media Mail & Expedited shipping is by USPS Priority Mail or equivalent;Read moreShow Less
2008 Hardcover Fine NO CD; No Access Code; Some Shelf Wear; Unless stated otherwise herein the notes, complementary books or items are not present; $20.00 minimum excluding ...shipping for orders to Puerto Rico & Hawaii; standard shipping is by USPS Media Mail & Expedited shipping is by USPS Priority Mail or equivalent;Read moreShow Less
Gain a strong conceptual understanding of statistics with the third edition of MODERN BUSINESS STATISTICS's balance of real-world applications and focus on the integrated strengths of Microsoft Excel 2007. 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 to perform the procedure. This integrated approach emphasizes the applications of Excel 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 2007 skills and understanding of business statistics that is simply EXCELlent!
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.
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. Statistical Inference about Means and Proportions with Two Populations. 11. Inferences about Population Variances. 12. Tests of Goodness of Fit and Independence. 13. Analysis of Variance and Experimental Design. 14. Simple Linear Regression. 15. Multiple Regression. 16. Regression Analysis: Model Building. 17. Nonparametric Methods. 18. Statistical Methods for Quality Control. 19. Decision Analysis. 20. Sample Survey (located on CD). 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: Using Excel Functions.