Spring, 3 Credits, 16-week Session, Tue/Thu 4:00 pm-5:15 pm, SEEC N129
Instructor: Julie Korak
This course focuses on experimental design and applied statistical methods for data analysis. Students will learn how to design and interpret experiments considering multiple variables, avoiding confounding effects, and identifying interactions between variables. The skills learned in this course are not specific to academic research. Practicing engineers use applied research techniques to troubleshoot and optimize systems, and the course topics are directly transferrable to those scenarios. These statistical tools are applied to analytical methods to validate environmental samples. Students will learn how to decipher analytical methods to ensure that environmental samples are collected and analyzed following robust QA/QC procedures. We will develop and apply these concepts using analytical methods commonly encountered in environmental engineering (e.g., organic carbon and spectroscopy).
Multilinear regression models
Response surface methodology
- Analytical chemistry methods
An undergraduate statistics course.
Design and Analysis of Experiments Douglas Montgomery, Wiley. (8th, 9th, or 10th edition).
The 8th edition is available online through CU on Knovel.com