Statistical Methods for Engineers, 3rd Ed. Este artículo no está disponible.Statistical Methods for Engineers, 3rd Ed

STATISTICAL METHODS FOR ENGINEERS, 3e, International Edition 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, students see how statistics fits within the methods of engineering problem solving. The text teaches students how to think like an engineer at analyzing real data and planning a project the same way they will in their careers. Case studies simulate problems students will encounter professionally and tackle on long-term job projects. The presentation makes extensive use of graphical analysis, and use of statistical software is encouraged for problem-solving to illustrate how engineers rely on computers for data analysis. The authors relate their own extensive professional experience as engineers in short margin notes called Voice of Experience that lend valuable context to how students will apply concepts in the field and why they're important to learn. And a rich companion website provides hours of multimedia lecture presentation narrated by the authors to show the material related live by different voices, simulating how students will listen and learn from multiple colleagues in their jobs.

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.