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Use of Minitab Statistical Analysis Software in Engineering Technology

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2019 ASEE Annual Conference & Exposition


Tampa, Florida

Publication Date

June 15, 2019

Start Date

June 15, 2019

End Date

June 19, 2019

Conference Session

ET Curriculum & Programs

Tagged Division

Engineering Technology

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Paper Authors


Ali Ahmad Louisiana Community and Technical College System-MEPOL

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Dr. Ali Ahmad is Director of Manufacturing Extension Partnership (MEP) of Louisiana, which operates under the Louisiana Community and Technical College System. Dr. Ahmad is a professional with over 18 years of experience in industrial engineering, research and management fields. He was previously an Associate Professor and Head of the Engineering Technology Department at Northwestern State University of Louisiana. He obtained his Ph.D. in Industrial Engineering from the University of Central Florida. Dr. Ahmad has diverse expertise in human-computer interaction, quality engineering, and simulating manufacturing systems. Ali worked on projects related to transfer of training, user-centered design, process improvement, and virtual environments. Dr. Ahmad is a Certified Simulation Analyst and a Certified Six Sigma Black Belt.

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The Engineering Technology curriculum provides wide spread knowledge in problem solving, management of resources, and process planning. Statistical decision-making is a key skill required by Engineering Technologists, and is required under ETAC of ABET program criteria for Industrial Engineering Technology and similarly named programs.

Traditional approaches to teaching statistical analysis tend to be mathematical in nature. Anecdotally, more than 75% of students dread their first Statistics class. This paper discusses the incorporation of Minitab Statistical Analysis Software in engineering technology courses. It looks at applying statistical decision-making without delving deep in statistical theory. It builds on industry specific approaches to empower non-statisticians to apply statistical tools in everyday decision-making. This is enabled using menu-driven statistical analysis software with powerful computational algorithms and graphics. Statistical analysis tools (such as descriptive statistics, confidence intervals, hypothesis testing, regression analysis, and ANOVA) can be applied using software, then, the decision-maker is able to use simple rules to interpret the software results. Moreover, the decision-maker can also test the assumptions of applying statistical tools, a process that is hard to teach in traditional Statistics courses. The paper concludes by providing directions for including real-life case studies to illustrate statistical decision-making to students.

Ahmad, A. (2019, June), Use of Minitab Statistical Analysis Software in Engineering Technology Paper presented at 2019 ASEE Annual Conference & Exposition , Tampa, Florida. 10.18260/1-2--33490

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