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Introducing Statistics To Mechanical Engineers In A Materials Science Course

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Conference

1998 Annual Conference

Location

Seattle, Washington

Publication Date

June 28, 1998

Start Date

June 28, 1998

End Date

July 1, 1998

ISSN

2153-5965

Page Count

8

Page Numbers

3.377.1 - 3.377.8

Permanent URL

https://peer.asee.org/7244

Download Count

25

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Paper Authors

author page

Scott R. Short

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

Session 1664

Session 1664

Introducing Statistics to Mechanical Engineers in a Materials Science Course

Scott R. Short, Ph.D., P.E. Northern Illinois University

Many schools are reducing the number of credit hours in undergraduate engineering programs so students have a better chance of graduating in four years. However, a majority of engineering educators feel that certain fundamental engineering topics such as materials engineering and statistics should be included in the curriculum. In an effort to minimize the number of credit hours required to graduate yet still cover these two important topics, the Department of Mechani- cal Engineering at Northern Illinois University is incorporating statistics in the laboratory section of their required materials science course. This match is a natural one because the laboratory projects require data acquisition, reduction, and statistical analysis. Probability paper plots and Rockwell hardness tests are used to introduce the student to the fundamental building block of statistics, the frequency distribution. An often-overlooked graphical statistical technique, the use of probability paper plots, is a potent teaching tool.

Introducing Statistics to Students

Statistics and its associated foundation of probability are vitally important in engineering. Engineers often must make decisions based upon relatively little information. Decision making requires fast, effective, and practical methods of data reduction and analysis and correlated meth- ods of feedback of the resulting conclusions. An understanding of the interrelationships between mathematics, processes, and statistics can contribute to improvements in data reduction analysis and problem-solving logic.1

The importance of statistics in engineering being a given, the critical issue becomes how to present this complex topic to undergraduates in a concise manner. Even the most introductory statistics textbooks are very mathematical in nature and contain a plethora of notation. Faced with having to learn statistics to complete their assigned materials science laboratory projects, most students succumb to the temptation to instead merely plug their data into a spreadsheet computer program (e.g., EXCEL) and command the software to perform a few basic canned statistical operations. Moreover, since most of the software statistical routines are based on the normal distribution, students are led to believe that if experimental data are not normally distrib- uted, then “something is wrong.” Simply put, the majority of undergraduates do not realize that the underlying foundation of statistics is the frequency (probability) distribution which may take any of several possible shapes depending on the processes and measurement techniques involved.

One of the most efficient ways to introduce undergraduates to frequency distributions and their associated statistics is through the use of probability paper plots (PPP). This often-overlooked

Short, S. R. (1998, June), Introducing Statistics To Mechanical Engineers In A Materials Science Course Paper presented at 1998 Annual Conference, Seattle, Washington. https://peer.asee.org/7244

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