Statistical Methods for Engineers

G Geoffrey Vining

ISBN 10: 0534384730 / ISBN 13: 9780534384739

Published by Cengage Learning, Inc, 2005

About this Item

STATISTICAL METHODS FOR ENGINERS 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.

Seller Inventory # CIN0534384730VG

Bibliographic Details

• Title: Statistical Methods for Engineers
• Publisher: Cengage Learning, Inc
• Publication Date: 2005
• Language: English
• ISBN 10: 0534384730
• ISBN 13: 9780534384739
• Binding: Hardcover
• Edition: 2nd Edition
• Condition: Very Good

About this title

Synopsis

STATISTICAL METHODS FOR ENGINEERS by Geoff Vining and Scott Kowalski presents real engineering data and takes a truly modern approach to statistics. An engineering case study runs throughout the text and gives conceptual continuity through each chapter. An excellent opening introduces students to the connection and the intimate link between statistical decision making and engineering.

About the Authors

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.