CHEE 209 Analysis of Process Data Units: 3.50
Statistical methods for analyzing and interpreting process data are discussed, . Topics include: role of data in assessing process operation, identifying major problems, graphical and numerical summaries, principles of valid inference, probability distributions for discrete and continuous data, and an introduction to linear regression analysis.
(Lec: 3, Lab: 0, Tut: 0.5)
(Lec: 3, Lab: 0, Tut: 0.5)
Requirements: Prerequisites: APSC 171 , APSC 172 , APSC 174
Corequisites:
Exclusions: STAT 268, STAT 269, MTHE 367
Offering Term: F
CEAB Units:
Mathematics 27
Natural Sciences 0
Complementary Studies 0
Engineering Science 15
Engineering Design 0
Offering Faculty: Smith Engineering
Course Learning Outcomes:
- Summarize visualize and interpret data using quantitative and graphical methods.
- Apply simple discrete probability models to analyze data related to quality such as particle size and to evaluate risk factors such as safety and environmental compliance.
- Apply continuous probability models to assist in decision-making with applications to quality improvement resource estimation safety and environmental compliance.
- Formulate confidence intervals and hypothesis tests for mean and variance using standard conditions, with applications including decision-making for quality improvement.
- Develop, estimate and analyze linear regression models to describe and predict process and laboratory behaviour.
- Use computer software to solve statistical problems.