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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)

PREREQUISITES:  APSC 171, APSC 172, APSC 174

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 include:

1. Summarize, visualize and interpret data using tabular and graphical methods.
2. 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.
3. Formulate confidence intervals and hypothesis tests for the sample average and sample variance under standard conditions.
4. Apply continuous probability models to assist in decision making with applications to quality improvement, resource estimation, safety and environmental compliance.
5. Apply computer intensive methods to extend applications of statistical methods to non-standard situations.
6. Develop and analyze linear models to describe and predict process and laboratory behavior.

This course assesses the following attributes:

• Knowledge Base, KB-MATH (CLO 1-5): Uses statistical methods to study, analyze, and interpret data obtained from chemical processes.
• Problem Analysis: Selects appropriate quantitative models, analyses, and boundary conditions to solve problems.