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Business Statistics in Practice, by Bruce Bowerman, Richard O'Connell
PDF Download Business Statistics in Practice, by Bruce Bowerman, Richard O'Connell
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The new edition of Business Statistics in Practice provides a modern, practical, and unique framework for teaching the first course in business statistics. This framework features case study and example-driven discussions of all basic business statistics topics. In addition, the authors have rewritten many of the discussions in this edition and have explained concepts more simply from first principles. The only prerequisite for this text is high school algebra.
- Sales Rank: #400210 in Books
- Published on: 2010-01-05
- Original language: English
- Number of items: 1
- Dimensions: 11.00" h x 1.40" w x 8.70" l, 4.60 pounds
- Binding: Hardcover
- 928 pages
- Used Book in Good Condition
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.
Most helpful customer reviews
4 of 4 people found the following review helpful.
This is a textbook about statistics
By Hoya Paranoia
This is a textbook about statistics. If you are buying it, it probably isn't because you're all like, "Oh, this book looks totally awesome. I'm going to get a copy and read it on the beach." More likely, you are a student and you have no other option. That being said, it is laid out in a logical manner and each chapter builds upon the last. The most useful sections are those that show you how to apply the concept being discussed in Excel. I kept mine rather than selling it after the class because the Excel sections are so useful.
3 of 3 people found the following review helpful.
Very comprehensive and informative statistics text
By Ellie Small
This is an excellent text book for beginning Statistics students as well as the more advanced.
The first few chapters are simple and a nice introduction to the subject. It then slowly builds up to the more advanced chapters, culminating in the chapters on multiple regression (chapter 14), model building (chapter 15), and time series forecasting (chapter 16).
These three chapters are not likely to be included in an introductory course in statistics, but are however of great interest for students who have had some statistics exposure to the subject already and wish to find out more. They are not easy chapters, but very interesting. A lot can be learned from them.
Chapter 17 is one of my favorites, as it goes into detail of process improvement, including some history. It describes statistical process control (SPC) and the advent of six sigma companies, complete with their success stories. It is a very real chapter that brings home the importance of statistics in general.
Particularly commendable is the attention this book gives to several different statistical packages, mainly Minitab and Excel (with the MegaStat add-in), explaining in detail the various variables displayed in those packages and their meaning.
This book, however, is not for mathematical statisticians, as in the later chapters a lot of the formulas are not presented. Instead the presence and meaning of the variables used is indicated and their calculation referred to the statistical packages. As an example, whereas the calculation of the coeefficients of the least squares line is presented for single variable regression, for multivariable regression it is not.
This is not, however, criticism. At this point, the calculations of the variables becomes so complicated, that presenting it will likely put off the audience for which this book is intended. Anyone interested in the complete calculations (mathematicians only) should consult a mathematical statistics book instead.
Overall, I think the book is a great read with lots of relevant examples and good explanations.
2 of 2 people found the following review helpful.
Terrible book: focuses on examples and not on general concepts
By Will C.
Absolutely terrible text book. Chapters are organized by examples and then describe the statistics formulas and procedures within the example. I have another statistics text book by Lind, Marchal, and Wathen that covers the exact same material for MBA level statistics, but clearly explains all concepts before moving on to examples. One specific example where this text is terrible, is one chapter fully explained several concepts, but all of the examples were of a positive value. On a test in the class, the professor asked what the significance of a negative value was. Thankfully he covered it in lectures (and it was covered in the Lind text), because this text didn't describe it at all!
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