Essentials of Business Statistics / Edition 4

Essentials of Business Statistics / Edition 4

ISBN-10:
007340182X
ISBN-13:
9780073401829
Pub. Date:
01/10/2011
Publisher:
McGraw-Hill Higher Education
ISBN-10:
007340182X
ISBN-13:
9780073401829
Pub. Date:
01/10/2011
Publisher:
McGraw-Hill Higher Education
Essentials of Business Statistics / Edition 4

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'Connell/Murphree/Orris-emphasize 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's 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: 01/10/2011
Edition description: Older Edition
Pages: 688
Product dimensions: 8.80(w) x 10.90(h) x 1.00(d)

About the Author

Richard T. O’Connell is associate professor of decision sciences at Miami University in Oxford, Ohio. He has more than 35 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. He also has extensive consulting experience and has taught workshops dealing with statistical process control and process improvement for a variety of companies in the Midwest. 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 16 textbooks. These include Forecasting and Time Series: An Applied Approach; Forecasting, Time Series, and Regression: An Applied Approach (also coauthored with Anne B. Koehler); and Linear Statistical Models: An Applied Approach. Professor O’Connell has published a number of articles in the area of innovative statistical education. 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. He has also given presentations on this subject at meetings such as the Joint Statistical Meetings of the American Statistical Association and the Workshop on Total Quality Management: Developing Curricula and Research Agendas (sponsored by the Production and Operations Management Society). Professor O’Connell received an M.S. degree in Decision Sciences from Northwestern University in 1973, and he is currently a member of both the Decision Sciences Institute and the American Statistical Association. In his spare time, Professor O’Connell enjoys fishing, collecting 1950s’ and 1960s’ rock music, and following the Green Bay Packers and Purdue University sports.

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.

Bruce L. Bowerman is 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 40 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 an Effective Educator award from the Richard T. Farmer School of Business Administration. Together with Richard T. O’Connell, Professor Bowerman has written 16 textbooks. These include Forecasting and Time Series: An Applied Approach; Forecasting, Time Series, and Regression: An Applied Approach (also coauthored with Anne B. Koehler); and Linear Statistical Models: An Applied Approach. The fi rst edition of Forecasting and Time Series earned an Outstanding Academic Book award from Choice magazine. Professor Bowerman has also published a number of articles in applied stochastic processes, time series forecasting, and statistical education. In his spare time, Professor Bowerman enjoys watching movies and sports, playing tennis, and designing houses.

Table of Contents

1. An Introduction to Business Statistics
2. Descriptive Statistics: Tabular and Graphical Methods
3. Descriptive Statistics: Numerical Methods
4. Probability
5. Discrete Random Variables
6. Continuous Random Variables
7. Sampling and Sampling Distributions
8. Confidence Intervals
9. Hypothesis Testing
10. Statistical Inferences Based on Two Samples
11. Experimental Design and Analysis of Variance
12. Chi-Square Tests
13. Simple Linear Regression Analysis
14. Multiple Regression and Model Building
Appendix A: Statistical Tables
Answers to Most Odd-Numbered Exercises
References
Photo Credits
Index
On the Website:
15. Process Improvement Using Control Charts
Appendix B: Properties of the Mean and the Variance of a Random Variable and the Co-variance
Appendix C: Derivatives of the Mean and Variance of x(bar) and p(hat)
Appendix D: Confidence Intervals for Parameters of Finite Populations
Appendix E: Logistic Regression

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