Essentials of Business Statistics / Edition 4

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Overview

The new edition of Essentials of Business Statistics delivers clear and understandable explanations of core business statistics concepts, making it ideal for a one-term course in business statistics. The author team—Bowerman/O&#39Connell/Murphree/Orris&#45emphasise the importance of interpreting statistical results to make effective decisions to improve business processes. The text offers real applications of statistics that are relevant to today&#39s business students which can be seen in the continuing case studies throughout the book. Continuing cases span throughout a chapter or even groups of chapters, easing students into new topic areas.

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Product Details

  • ISBN-13: 9780073401829
  • Publisher: McGraw-Hill Higher Education
  • Publication date: 1/10/2011
  • Edition description: Older Edition
  • Edition number: 4
  • Pages: 688
  • Sales rank: 755,608
  • Product dimensions: 8.80 (w) x 10.90 (h) x 1.00 (d)

Meet the Author

Bruce L. Bowerman is a professor of decision sciences at Miami University in Oxford, Ohio. He received his Ph.D. degree in statistics from Iowa State University in 1974, and he has over 37 years of experience teaching basic statistics, regression analysis, time series forecasting, survey sampling, and design of experiments to both undergraduate and graduate students. In 1987 Professor Bowerman received an Outstanding Teaching award from the Miami University senior class, and in 1992 he received and Effective Educator award from the Richard T. Farmer School of Business Administration. Together with Richard T. O’Connell, Professor Bowerman has written 11 textbooks. These include Forecasting and Time Series: An Applied Approach and Forecasting, Time Series, and Regression: An Applied Approach (also coauthored with Anne B. Koehler); The first edition of Forecasting and Time Series earned an Outstanding Academic Book award from Choice magazine.

Richard T. O'Connell is an associate professor of decision sciences at Miami University in Oxford, Ohio. He has more than 32 years of experience teaching basic statistics, statistical quality control and process improvement, regression analysis, time series forecasting, and design of experiments to both undergraduate and graduate business students. In 2000 Professor O’Connell received an Effective Educator award from the Richard T. Farmer School of Business Administration. Together with Bruce L. Bowerman, he has written seven textbooks. These include Forecasting and Time Series: An Applied Approach and Linear Statistical Models: An Applied Approach. He is one of the first college instructors in the United States to integrate statistical process control and process improvement methodology into his basic business statistics course. He (with Professor Bowerman) has written several articles advocating this approach.

James Burdeane “Deane” Orris

J.B. Orris is a professor of management science at Butler University in Indianapolis, Indiana. He received his Ph.D. from the University of Illinois in 1971, and in the late 1970s with the advent of personal computers, he combined his interest in statistics and computers to write one of the first personal computer statistics packages—MICROSTAT. Over the past 20 years, MICROSTAT has evolved into MegaStat, which is an Excel add-in statistics program. In 1999 he wrote an Excel book (Essentials: Excel 2000 Advanced) and has done work in neural networks, spreadsheet simulation, and statistical analysis for many research projects. He has taught statistics and computer courses in the College of Business Administration of Butler University since 1971. He is a member of the American Statistical Association and is past president of the Central Indiana Chapter. In his spare time, Professor Orris enjoys reading, working out, and working in his woodworking shop.

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Table of Contents

1. An Introduction to Business Statistics2. Descriptive Statistics: Tabular and Graphical Methods3. Descriptive Statistics: Numerical Methods4. Probability5. Discrete Random Variables6. Continuous Random Variables7. Sampling and Sampling Distributions8. Confidence Intervals9. Hypothesis Testing10. Statistical Inferences Based on Two Samples11. Experimental Design and Analysis of Variance12. Chi-Square Tests13. Simple Linear Regression Analysis14. Multiple Regression and Model BuildingAppendix A: Statistical TablesAnswers to Most Odd-Numbered ExercisesReferencesPhoto CreditsIndexOn the Website: 15. Process Improvement Using Control ChartsAppendix B: Properties of the Mean and the Variance of a Random Variable and the Co-varianceAppendix C: Derivatives of the Mean and Variance of x(bar) and p(hat)Appendix D: Confidence Intervals for Parameters of Finite PopulationsAppendix E: Logistic Regression

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