機率統計 >> 商業統計 >> Statistics for Business & Economics 2006 (CD Inside) 作者：Anderson 年份：2006年 1版 ISBN：9867497821 書號：PS0285HC 規格：精裝/彩色 頁數：1022 出版商：Cengage 定價：$1,100元 線上價：$990元 參考網址：http://websites.swlearning.com/cg...   This market leading text offers a proven, comprehensive, applications-oriented approach. Written by authors who are highly regarded in the field, the text provides sound methodological development. The discussion and development of each technique is presented in an application setting, with the statistical results providing insights to decisions and solutions to problems. Statistics for Business and Economics, 9e offers proven accuracy that has led instructors to adopt it simply for its superior examples and exercises alone. David R. Anderson David R. Anderson is Professor of Quantitative Analysis in the College of Business Administration at the University of Cincinnati. Born in Grand Forks, North Dakota, he earned his BS, MS, and PhD 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. In addition to teaching 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 been honored with nominations and awards for excellence in teaching and excellence in service to student organizations. He has coauthored ten textbooks related to decision sciences and actively consults with businesses in the areas of sampling and statistical methods. Dennis J. Sweeney Dennis J. Sweeney is Professor of Quantitative Analysis and founder of the Center for Productivity Improvement at the University of Cincinnati. Born in Des Moines, Iowa, he earned BS and BA degrees from Drake University, graduating summa cum laude. He received his MBA and DBA degrees from Indiana University, where he was an NDEA Fellow. Dr. Sweeney has worked in the management science group at Procter & Gamble and has been a visiting professor at Duke University. Professor Sweeney served five years 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. He 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. Professor Sweeney has coauthored ten textbooks in the areas of statistics, management science, linear programming, and production and operations management. Thomas A. Williams Thomas A. Williams is Professor of Management Science in the College of Business at Rochester Institute of Technology (RIT). Born in Elmira, New York, 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 first undergraduate program in Information Systems. At RIT, he was the first chair of the Decision Sciences Department. Professor Williams is the coauthor of 11 textbooks in the areas of management science, statistics, production and operations management, and mathematics. He has been a consultant for numerous Fortune 500 companies in areas ranging from the use of elementary data analysis to the development of large-scale regression models. Juei-Chao Chen, Fu Jen Catholic University 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 Testing. 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. Index Numbers. 18. Forecasting. 19. Nonparametric Methods. 20. Statistical Methods for Quality Control. 21. Decision Analysis. 22. Sample Survey (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. Index. 統計學(Anderson 2006) (CD Inside)