Analysis of Process Data





Kody KazdaDUP
Abby LiuDUP
Rutendo MutambanengweDUP
Seyed Moein MousaviDUP

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)


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:

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)
TOO (b)

CLO6 Develop and analyze linear models to describe and predict process and laboratory behavior. KB Math (b)

PA (c)
PA (f)
TOO (b)

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

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”.

Course Structure and Activities

3 lecture hours + 1 tutorial hour per week.  Please refer to Solus for times and locations.


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.