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Session 2247

DATA ANALYSIS IN ENGINEERING TECHNOLOGY James E. Maisel East Campus, Arizona State University Mesa, AZ 85206

Abstract

A data analysis graduate/undergraduate course has been developed in the Department of Electronics and Computer Engineering Technology at the East Campus of Arizona State University. Various statistical techniques are explored to show the relevance and importance of extracting important information from raw data.

Introduction

Data analysis has permeated essentially all industrial processes. With data retrieval systems available, large amounts of data can be stored and viewed later for analysis. Raw data sets have to be processed to characterize the important data features buried in the raw data. This is where data analysis plays a key role.

Data processing is becoming a very important facet for engineering technologists. At some point in their professional career, they will be faced with using data analysis or using the results of data analysis to study the behavior of a manufacturing process [1]. In either case, their expertise in data analysis may give them the competitive edge in industry.

The Department of Electronics and Computer Engineering Technology at Arizona State University introduced a new course this past year called Data Analysis. It assumes that the engineering technologist has a rudimentary background in probability and statistics, and has senior or graduate departmental standing. A data analysis project, with a written report, differentiates the graduate from the undergraduate student.

Topics in data analysis involve tedious calculations when the data sets become large. Thus, hand calculations are restricted to very small data sets and are used to demonstrate the significance of a particular statistic.

Once the students understand the basics of, and the significance of data analysis, they are ready to use a statistical software package. As a homework assignment, they start by doing a small data set analysis using hand calculations and a software package. A comparison of results gives the students confidence in data analysis. Matlab along with Statistics Toolbox TM was adopted because the students are familiar with Matlab from other courses taught in the department.

Table I lists the more important topics covered in the course.

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Maisel, J. E. (1997, June), Data Analysis In Engineering Technology Paper presented at 1997 Annual Conference, Milwaukee, Wisconsin. 10.18260/1-2--6486