Essentials of Business Statistics https://www.mheducation.com/cover-images/Jpeg_400-high/0078020530.jpeg 5 9780078020537 The primary goal of Essentials of Business Statistics is to illustrate an accurate view of business statistics in a way that students can easily understand. This is achieved in the following ways: New statistical topics and tools are introduced by using continuing case studies. This approach helps to alleviate student anxiety in learning new concepts and enhances overall comprehension Streamlined and clarified coverage of graphical and numerical methods New graphically based procedures for finding confidence intervals and performing hypothesis tests Increased emphasis on Excel and MINITAB with improved and updated step-by-step instructions in the end of chapter material Connect Business Statistics homework management Connect is the only integrated learning system that empowers students by continuously adapting to deliver precisely what they need, when they need it, and how they need it, so that your class time is more engaging and effective.
Essentials of Business Statistics

Essentials of Business Statistics

5th Edition
By Bruce Bowerman and Richard O'Connell and Emily Murphree and J. Burdeane Orris
ISBN10: 0078020530
ISBN13: 9780078020537
Copyright: 2015
09780078020537

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The estimated amount of time this product will be on the market is based on a number of factors, including faculty input to instructional design and the prior revision cycle and updates to academic research-which typically results in a revision cycle ranging from every two to four years for this product. Pricing subject to change at any time.

Program Details

Chapter 1 An Introduction to Business Statistics

Chapter 2 Descriptive Statistics: Tabular and Graphical Methods

Chapter 3 Descriptive Statistics: Numerical Methods

Chapter 4 Probability

Chapter 5 Discrete Random Variables

Chapter 6 Continuous Random Variables

Chapter 7 Sampling and Sampling Distributions

Chapter 8 Confidence Intervals

Chapter 9 Hypothesis Testing

Chapter 10 Statistical Inferences Based on Two Samples

Chapter 11 Experimental Design and Analysis of Variance

Chapter 12 Chi-Square Tests

Chapter 13 Simple Linear Regression Analysis

Chapter 14 Multiple Regression and Model Building

Appendix A Statistical Tables

Answers to Most Odd-Numbered Exercises

Preferences

Photo Credits

Index

Chapter 15 Process Improvement Using Control Charts

About the Author

Bruce Bowerman

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.

Richard O'Connell

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.

Emily Murphree

Emily S. Murphree Emily S. Murphree is associate professor of statistics in the Department of Mathematics and Statistics at Miami University in Oxford, Ohio. She received her Ph.D. degree in statistics from the University of North Carolina and does research in applied probability. Professor Murphree received Miami’s College of Arts and Science Distinguished
Educator Award in 1998. In 1996, she was named one of Oxford’s Citizens of the Year for her work with Habitat for Humanity and for organizing annual Sonia Kovalevsky Mathematical Sciences Days for area high school girls. Her enthusiasm for hiking in wilderness areas of the West motivated her current research on estimating animal population sizes.

J. Burdeane Orris

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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