Statistical Methods for Engineers
G. Geoffrey Vining, Scott Kowalski
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Language: English
Published by Duxbury Pr, 2010
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[ No Hassle 30 Day Returns ][ Ships Daily ] [ Underlining/Highlighting: NONE ] [ Writing: NONE ] [ Edition: third ] Publisher: Duxbury Press Pub Date: 1/1/2010 Binding: Hardcover Pages: 618 third edition.
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- Title
- Statistical Methods for Engineers
- Author
- G. Geoffrey Vining, Scott Kowalski
- Publisher
- Duxbury Pr
- Publication year
- 2010
- Condition
- Good
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 053873518X
- ISBN 13
- 9780538735186
- Edition
- 3rd Edition
STATISTICAL METHODS FOR ENGINEERS offers a balanced, streamlined one-semester introduction to Engineering Statistics that emphasizes the statistical tools most needed by practicing engineers. Using real engineering problems with real data based on actual journals and consulting experience in the field, users see how statistics fits within the methods of engineering problem solving. The book teaches users how to think like an engineer at analyzing real data and planning a project the same way they will in their careers.
"Synopsis" may belong to another edition of this title.
About the Author
Dr. Geoffrey Vining received his Ph.D. from Virginia Tech., Blacksburg. He is a Professor and Department Head in the Statistics Department at Virginia Tech. He also served on the faculty of the Statistics Department at the University of Florida, Gainesville, as a practicing engineer with the Faber-Castell Corporation and as an industrial consultant.
Dr. Scott Kowalski received his Ph.D. from the University of Florida, Gainesville. He works as a Technical Trainer at Minitab, Inc. where he mentors Minitab's International Partners on their training efforts and teaches statistics to corporations in the United States, Asia and Australia. Prior to joining Minitab he taught at Stetson University and University of Central Florida. Dr. Kowalski is a Senior Member of ASQ, a member of the American Statistical Association, an Associate Editor for Quality Technology and Quantitative Management, and serves on the Editorial Review Board for the Journal of Quality Technology and Quality Engineering. Along with co-author Geoffrey Vining he was awarded the 2005 Nelson Award winner for paper with the "greatest immediate impact to practitioners" by the Journal of Quality Technology.
Dr. Scott Kowalski received his Ph.D. from the University of Florida, Gainesville. He works as a Technical Trainer at Minitab, Inc. where he mentors Minitab's International Partners on their training efforts and teaches statistics to corporations in the United States, Asia and Australia. Prior to joining Minitab he taught at Stetson University and University of Central Florida. Dr. Kowalski is a Senior Member of ASQ, a member of the American Statistical Association, an Associate Editor for Quality Technology and Quantitative Management, and serves on the Editorial Review Board for the Journal of Quality Technology and Quality Engineering. Along with co-author Geoffrey Vining he was awarded the 2005 Nelson Award winner for paper with the "greatest immediate impact to practitioners" by the Journal of Quality Technology.
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