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Nov 21, 2024
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IE 203 - Applications of Statistics in Industrial Engineering2 lecture hours 2 lab hours 3 credits
Course Description
This course emphasizes the importance and relevance of statistics in the field of Industrial Engineering. The purpose of the course is to further student understanding of applications of statistics in engineering. The course will concentrate on data collection, analysis and inference using statistical methods. A state-of-the-art statistics package will be used so that meaningful problems can be addressed. The course will provide instruction in the use of these tools and laboratory time to practice their use while deepening understanding and expertise. (prereq: MA 262 )
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• describe and define basic statistical terminology
• perform statistical analyses including identifying and working with probability distributions
• understand how and why statistics are an integral part of an engineering analysis
• draw inferences from data obtained by testing components and systems
• improve communications skills, both written and verbal
• understand the value of life-long learning and personal growth and development
Prerequisites by Topic
• Good understanding of probability, statistical distributions, hypothesis testing, and analysis of variance
Course Topics
• Minitab (1 week)
• Measurement error and propagation (1 week)
• Confidence intervals (1 week)
• Hypothesis testing (2 weeks)
• Correlation and linear regression (2 weeks)
• Multiple regression (1 week)
• Experimental design (2 weeks)
Laboratory Topics
• A weekly two-hour lab will use defined projects to exercise student skills as defined in the Course Outcome section
Coordinator
Aaron Armstrong
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