CHEE 209 is an introductory course in probability and statistics and develops skills that are essential to engineers of all disciplines. Students from Geological Engineering, Chemical Engineering, Engineering Chemistry and Mining Engineering take this course. Examples from these disciplines will be used to demonstrate the various techniques. The skills acquired in this course are further developed in a more advanced course, CHEE 418 “Strategies for Process Investigations”.
Analysis of Process Data
Personnel
Instructor
| Xiang Li | 403 | xiang.li@queensu.ca | 613-533-6582 |
TAs
| Kody Kazda | DUP G37 | 17kk18@queensu.ca | |
| Abby Liu | DUP B16 | ql9@queensu.ca | |
| Rutendo Mutambanengwe | DUP B16 | 15rlm3@queensu.ca | |
| Seyed Moein Mousavi | DUP B16 | s.mousavi@queensu.ca |
Course Description
Statistical methods for analyzing and interpreting process data are discussed, with special emphasis on techniques for continuous improvement of process operations. 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, process capability, comparing process performance to target values, comparing performances of two processes, control charts, and an introduction to linear regression analysis.
(27/0/0/15/0) (Mathematics/Natural Sciences/Complementary Studies/Engineering Science/Engineering Design)
PREREQUISITES: APSC 171, APSC 172, APSC 174
Objectives and Outcomes
The objective of this course is to develop competencies in the use of statistical tools for the analyses of data typically encountered by chemical, geological and mining engineers and engineering chemistry students and graduates. These techniques can be used to analyze laboratory and field data, as well as operating data obtained from industrial processes.
Specific course learning outcomes (CLO) include:
| CLO | DESCRIPTION | INDICATORS |
| CLO1 | Summarize, visualize and interpret data using tabular and graphical methods. | KB Math (b) |
| CLO2 | Apply simple discrete probability models to analyze data related to quality such as particle size and ore concentration, and to evaluate risk factors such as safety and environmental compliance. | KB Math (b)
PA (c) |
| CLO3 | Formulate confidence intervals and hypothesis tests for the sample average and sample variance under standard conditions. | KB Math (b) |
| CLO4 | Apply continuous probability models to assist in decision making with applications to quality improvement, resource estimation, safety and environmental compliance. | KB Math (b)
PA (f) |
| CLO5 | Apply computer intensive methods to extend applications of statistical methods to non-standard situations. | KB Math (b)
PA (c) |
| CLO6 | Develop and analyze linear models to describe and predict process and laboratory behavior. | KB Math (b)
PA (c) |
This course develops the following attributes at the 2nd year level:
Knowledge Base (KB): Math (b) Applies numerical and statistical methods to analyze, interpret and model data.
Problem Analysis (PA): (c) Develop and interpret a model for solving complex engineering problems. (f) Evaluates and analyzes solutions to complex engineering problems in order to reach conclusions.
Engineering Tools (TOO): (b) Apply and manage appropriate techniques, apparatus, databases, models, tools, and/or processes to accomplish a task.
Relevance to the Program
Course Structure and Activities
3 lecture hours + 1 tutorial hour per week. Please refer to Solus for times and locations.
Resources
Textbook: Miller & Freund's Probability and Statistics for Engineers, 8th or 9th edition, Richard A. Johnson (author)
Note: This is an expensive textbook, but it is one that will be a valuable resource for many courses and into your work life beyond Queen's.
All course lecture slides, assignments and tutorials will be posted on the CHEE 209 course site administered through OnQ.