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The Use Of Numerical Propagation Of Error Analyses In Experimental Design

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1999 Annual Conference


Charlotte, North Carolina

Publication Date

June 20, 1999

Start Date

June 20, 1999

End Date

June 23, 1999



Page Count


Page Numbers

4.545.1 - 4.545.12

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Paper Authors

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Nancy Peck

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John E. Nydahl

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NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract

Session 3420

The Use of Numerical Propagation of Error Analyses in Experimental Design

John Nydahl and Nancy Peck Department of Mechanical Engineering, University of Wyoming


The importance of statistics in engineering is not disputed, but how to effectively take it from a meaningless ritual to a truly interesting and integral part of a laboratory is disputed, especially at the introductory level. The current paper describes a simplified statistical procedure that is used in a sophomore level laboratory course that permits students to easily couple a propagation of error analysis to a system’s theoretical model. This is accomplished through the use of the function capability that modern spreadsheets possess. In this case, a Visual Basic function macro is written to calculate the desired experimental result in terms of the mean values of its measured parameters. This function is then used to numerically estimate the variance of the result with respect to each of its measured properties and, therefore, its respective sensitivity to errors in each of the measurements, as well as the experiment’s maximum probable error. This technique permits the investigation of more complex and realistic systems in a beginning laboratory. It also permits the use of experimental design both to determine what instrumentation should be used and how to configure the apparatus to minimize the resulting error. Embedding this uncomplicated technique in a spreadsheet environment is very helpful to the student since spreadsheets are the natural experimental platform for data presentation and reduction, and this software already possesses various statistical packages. The details of an example with four degrees of freedom are documented.

I. Introduction

In 1992, University of Wyoming’s College of Engineering completed an internal review in which a questionnaire was sent to alumni who graduated in the last decade 1. Most reported that they were adequately prepared to compete with their colleagues but recommended that more “real world” engineering tasks be incorporated in future curriculums. These tasks included the development of better oral and written communication skills plus more exposure to computer tools (engineering graphics, computer programming, spreadsheets and word processing), engineering statistics, teamwork, and general management. The Mechanical Engineering Department (ME) immediately initiated a major effort to integrate these constructive criticisms throughout its curriculum. Many of these suggestions are also delineated in the new Accreditation Board of Engineering and Technology (ABET) 2000 criteria2. The UW’s

Peck, N., & Nydahl, J. E. (1999, June), The Use Of Numerical Propagation Of Error Analyses In Experimental Design Paper presented at 1999 Annual Conference, Charlotte, North Carolina.

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