## Materials Science Experiments And Engineering Statistics

Conference

2003 Annual Conference

Location

Nashville, Tennessee

Publication Date

June 22, 2003

Start Date

June 22, 2003

End Date

June 25, 2003

ISSN

2153-5965

Conference Session

Materials Curricula: Modeling & Math

Page Count

9

Page Numbers

8.838.1 - 8.838.9

DOI

10.18260/1-2--11618

Permanent URL

https://peer.asee.org/11618

270

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

Session 2464

Materials Science Experiments and Engineering Statistics

Surendra K. Gupta and Carol E. Marchetti Rochester Institute of Technology

Abstract

This paper describes three of the five engineering modules being developed for use in three statistics courses: 314 – Engineering Statistics, 351 – Probability & Statistics I, and 352 – Probability & Statistics II. 314 is a mandatory course for all mechanical engineering (BSME) students; 351 & 352 are mandatory for all industrial & systems (BSIE) engineering students. To answer a student’s (often unasked) question “why should I learn this?” in these courses, we sought to develop several engineering application modules. The intent of these modules is to provide the student with context for statistics concepts and the motivation to learn them.

The only engineering courses with hands-on lab experience that all BSME & BSIE students take before or concurrently with these statistics courses are 343 – Materials Processing and 344 – Materials Science. Consequently, we chose experiments or experimental data from these two materials courses for designing the modules. Funding from a Provost’s Learning Innovations Grant is providing support for a materials science and a statistics professor in development of these five modules.

Statistics textbooks have data from engineering applications, but the problems tend to be simplistic in nature. From the one or two sentences of background information that are usually provided with textbook problems, it is difficult to understand why someone would want to collect and analyze this data. We have created modules consisting of more complete problems, including why someone would want to examine this type of data and how the statistical method used will provide a solution. Each stand-alone module contains a background and description of an engineering problem. In some cases data is provided, in others the mechanism for data collection is provided. Statistical processing of data, presentation of reduced results, and interpretation are a part of each module. The modules can be assigned to students individually or in teams.

The first module is a hands-on kit to collect mass, diameter and thickness data of a set of 100 new pennies and 100 old pennies. Statistical analysis of data is then combined with interpretation to explain the differences between the new and old pennies. The second module involves a collection of Rockwell hardness data on several samples of hardened tool steel, and statistical methodology is used to predict probable range of hardness values of the next sample. The third module involves collecting load versus indentation size data in micro-hardness testing of a polished steel specimen, and statistical method is used to determine the uncertainty in the resulting hardness values.

Proceedings of the 2003 American Society of Engineering Education Annual Conference & Exposition Copyright © 2003, American Society of Engineering Education

Gupta, S. (2003, June), Materials Science Experiments And Engineering Statistics Paper presented at 2003 Annual Conference, Nashville, Tennessee. 10.18260/1-2--11618

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