400212.0 Design of Experiments (5 cr)
Cooperation network course
Network: Cross-institutional studies in advanced courses in mathematics and statistics
This course is offered through the Network for Advanced Studies in Mathematics. These studies are available for the following degree students:
- Bachelor's Degree Programme in Mathematics
- Master's Degree Programme in Mathematics
- Bachelor's Degree Programme in Mathematics (Subject Teacher)
- Master's Degree Programme in Mathematics (Subject Teacher)
- Bachelor's Degree Programme in Mathematics, Chemistry or Physics Subject Teacher Education and Primary Teacher Education (Specialication in Mathematics)
- Master's Degree Programme in Mathematics, Chemistry or Physics Subject Teacher Education and Primary Teacher Education (Specialication in Mathematics)
- Doctoral Programme in Mathematics and Statistics
- Doctoral Programme in Mathematics and Science (Specialication in Mathematics)
Grading scale:
0-5
Description
The main point of the course is to learn the modern response surface aproach to modeling and analyzing processes in engineering. The course is practical in the sense that we use Matlab for planning and analyzing experiments, and for optimizing processes. Some methods for judging different reliability aspects of the results are given, mainly using residual analysis and statistical tests. The analyses are to be reported in writing, and the participants anonymously assess the reports of their peers.
Learning outcomes
In order to pass the course, the student is expected to be able to plan and carry out statistical analyses of engineering processes and optimize the same using statistical methods. Moreover, reporting of the obtained results, in written and oral form, is a part of the course.
Generic skills practiced in the course: Writing mathematically intensive reports, assessing peers' work against given criteria, presentation skills (probably in video format), computing with uncertain and incomplete information
(Videos are becoming more common in job recruiting situations.)
Additional information
Course web page: http://www.users.abo.fi/mkurula/fplan.html
Attending the computer exercises is compulsory.
The course is very intensive, so it is not a good idea to take too many other courses at the same time. Estimated course workload is 15-20h per week.
Description of prerequisites
Many participants find the course challenging and intensive.
Minimal background is:
Introductory courses in probability and inferential statistics (can be the same course)
Some course that includes basic matrix theory