The Sixth Edition of ESSENTIALS OF STATISTICS FOR BUSINESS AND ECONOMICS is an introductory statistics book that emphasizes essential statistical concepts and their practical business applications. The discussion and development of each technique are geared toward real-world applications, with the statistical results providing insights for decisions and solutions related to common business problems. The easy-to-follow presentation style and proven problem-scenario approach clearly show how to apply statistical methods in practical business situations. This brief introduction to business statistics provides both a conceptual understanding of statistics and real-world applications of statistical methodology.
"Excellent problem sets and answers in back of book - vivid color (maintains student interest better) - thorough discussion and examples."- Gary Black, University of Southern Indiana
"1. Statistics presented in plain language, easily followed. 2. Good examples that closely follow the text discussion. 3. Well constructed homework questions that coincide with the text. 4. Tables that are easy to read." - Joseph Williams, Hawamba Community College
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. Comparisons Involving Means, Experimental Design, and Analysis of Variance. 11. Comparisons Involving Proportions and a Test of Independence. 12. Simple Linear Regression. 13. Multiple Regression. 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. Appendix F: Computing p-Values Using Minitab and Excel.