This best-selling text teaches students how to apply statistics to real business problems through the authors' unique approach. Keller and Warrack teach students a three-step approach to problem solving: to identify the right technique by focusing on the relationship between the problem and the data; to solve the problem by hand calculation, or by using Microsoft® Excel or MINITAB; and to interpret the results. Step-by-step instructions for both Excel and MINITAB are integrated throughout the book. This approach offers maximum flexibility to instructors wishing to teach concepts primarily by hand or with the computer (Excel or MINITAB) or by using both computer and hand calculation methods.
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About the Author
Dr. Gerald Keller is Emeritus Professor of Business at Wilfrid Laurier University, where he taught statistics, management science, and operations management from 1974 to 2011. He also taught at the University of Toronto, the University of Miami, McMaster University, the University of Windsor, and the Beijing Institute of Science and Technology. In addition to consulting with banks on credit scoring and credit card fraud, Dr. Keller has conducted market surveys for the Canadian government on energy conservation. His books include BSTAT, 2e, APPLIED STATISTICS WITH MICROSOFT EXCEL, ESSENTIALS OF BUSINESS STATISTICS (co-authored), AUSTRALIAN BUSINESS STATISTICS (co-authored), and STATISTICS LABORATORY MANUAL EXPERIMENTS USING MINITAB. Dr. Keller also has been published in OMEGA, IIE TRANSACTIONS, DECISION SCIENCES, INFOR, ECONOMICS LETTERS, and ARCHIVES OF SURGERY.
Table of Contents1. What Is Statistics?. PART I: DESCRIPTIVE TECHNIQUES AND PROBABILITY . 2. Graphical Descriptive Techniques. 3. Art and Science of Graphical Presentations. 4. Numerical Descriptive Measures . 5. Data Collection and Sampling. 6. Probability and Discrete Probability Distributions. 7. Continuous Probability Distributions. PART II. STATISTICAL INFERENCE. 8. Sampling Distributions. 9. Introduction to Estimation . 10. Introduction to Hypothesis Testing. 11. Inference about the Description of A Single Population. 12. Inference about the Comparison of Two Populations. 13. Statistical Inference: A Review of Chapters 11 and 12. 14. Analysis Of Variance . 15. Additional Tests For Qualitative Data . 16. Simple Linear Regression and Correlation. 17. Multiple Regression. PART III. APPLICATIONS. 18. Statistical Process Control. 19. Statistical Inference: Conclusion. Index. Index Of Computer Instructions.