Statistical Methods for Engineers

Vining, G. Geoffrey; Kowalski, Scott

ISBN 10: 053873518X / ISBN 13: 9780538735186

Verlag: Cengage Learning, 2010

Beschreibung

This copy may contain significant wear, including bending, heavy writing, tears, and or water damage. This book is a functional copy, not necessarily a beautiful copy. Copy may have loose pages. May not include access codes or CDs. May be an Ex library book with stickers and stamps. Dustjacket may be missing.

Bestandsnummer des Verkäufers GBV.053873518X.A

Bibliografische Details

• Titel: Statistical Methods for Engineers
• Verlag: Cengage Learning
• Veröffentlichungsdatum: 2010
• Sprache: Englisch
• ISBN-10: 053873518X
• ISBN-13: 9780538735186
• Bindung: Hardcover
• Ausgabe: 3. Auflage
• Zustand: acceptable

Über diesen Titel

Inhaltsangabe

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.

Reseña del editor

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, 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.