Language : English
Published : 2016
Pages : 158
Statistics for Applied Science
This text covers the essential topics needed for a fundamental understanding of basic statistics and its applications in the fields of engineering and the sciences. Interesting, relevant applications use real data from actual studies, showing how the concepts and methods can be used to solve problems in the field. The authors assume one semester of differential and integral calculus as a prerequisite.
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 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.
About 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.
This book emphasizes the basics of statistics and its application. The concepts are explained in clear and simple language, with the aid of illustrative examples, charts and diagrams.
- Chapter 1. Introduction to Statistics
- Chapter 2. Data Presentation
- Chapter 3. Measures of Central Tendency
- Chapter 4. Measures of Dispersion
- Chapter 5. Index Number
- Chapter 6. Correlation and Regression
- Chapter 7. Time Series Data Analysis