Introductory Statistics for Engineering Experimentation
Academic Press
Published on 25. September 2003
Book
Hardback
528 pages
978-0-12-515423-9 (ISBN)
Description
The Accreditation Board for Engineering and Technology (ABET) introduced a criterion starting with their 1992-1993 site visits that "Students must demonstrate a knowledge of the application of statistics to engineering problems." Since most engineering curricula are filled with requirements in their own discipline, they generally do not have time for a traditional two semesters of probability and statistics. Attempts to condense that material into a single semester often results in so much time being spent on probability that the statistics useful for designing and analyzing engineering/scientific experiments is never covered. In developing a one-semester course whose purpose was to introduce engineering/scientific students to the most useful statistical methods, this book was created to satisfy those needs.
More details
Language
English
Place of publication
San Diego
United States
Publishing group
Elsevier Science Publishing Co Inc
Target group
Professional and scholarly
Provides students and practitioners with the statistical tools needed to design and analyze engineering experiments and problems
Dimensions
Height: 229 mm
Width: 152 mm
Weight
830 gr
ISBN-13
978-0-12-515423-9 (9780125154239)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Peter R. Nelson | Karen A. F. Copeland | Marie Coffin
Introductory Statistics for Engineering Experimentation
E-Book
09/2003
Academic Press
€93.95
Available for download
Persons
By Dr. Peter R. Nelson, Dr. Karen A.F. Copeland and Marie Coffin
Author
Professor of Mathematical Sciences, Clemson University, USA
Statistical Consultant; Boulder, CO, USA
Paradigm Genetics Inc., Cary, NC, USA
Content
Introduction; Summarizing Data; Models for Experiment Outcomes; Models for the Random Error; Inference for a Single Population; Comparing Two Populations; One-Factor Multi-Sample Experiments; Experiments with Two Factors; Multi-Factor Experiments; Inference for Regression Models; Response Surface Methods; Appendices; References.