Statistics for Business and Economics

David R. Anderson is Professor of Quantitative Analysis in the College of Business Administration at the University of Cincinnati, USA. 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. Eddie Shoesmith is formerly Senior Lecturer in Statistics and formerly Programme Director for undergraduate business and management programmes in the School of Business, University of Buckingham, UK. Jim Freeman is Senior Lecturer in Statistics and Operational Research at Manchester Business School, UK. In July 2008 he was appointed Editor of the Operational Research Societys OR Insight journal. 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.

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. Time Series Analysis and Forecasting
18. Non-parametric Methods