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Course Catalog 2010-2011
MAT-51646 Design of Experiments, 4 cr |
Person responsible
Keijo Ruohonen
Lessons
| Study type | P1 | P2 | P3 | P4 | Summer | Implementations | Lecture times and places |
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Requirements
Closed-book written exam.
Completion parts must belong to the same implementation
Learning outcomes
After completing the course the student is able to model and design experiments so as to make them economical without detracting from the power of statistical analyses. Since the course is a self-study course, the student may choose the material to emphasize either response surface modelling, with a collection of standard designs, in particular response optimization, or categorical ANOVA analysis methods, or small sampling designs. The student will also be familiar with the DOE tools in a statistical program (MATLAB, JMP, R or some such). Nowadays these methods form a long-standing well-researched and much used, and therefore it is simply not possible to include outcomes for them all within a single course. Completing the course the student nevertheless should be able the generalize and extend the skills.
Content
| Content | Core content | Complementary knowledge | Specialist knowledge |
| 1. | Basics of regression analysis and ANOVA. Basic types of designs. | ||
| 2. | Response optimization methods. | ||
| 3. | Standard (optimal) experimental designs, e.g. Simplex, Plackett-Burman, 2k, CCD, and D-optimum experiments. | ||
| 4. | Use of a statistical program (MATLAB, JMP, R). | ||
| 5. | Small sampling methods. |
Evaluation criteria for the course
Final grade is determined from a closed-book exam. Passing the course requires passing the final exam, and for this at most half of the maximum points are required. Mastering basic methods of the core content should be sufficient for passing the course with grade 3. To get the degree 4 a more thorough mastering is required, getting the grade 5 then requires skills of using this knowledge in new modelling situations.
Assessment scale:
Numerical evaluation scale (1-5) will be used on the course
Partial passing:
Study material
| Type | Name | Author | ISBN | URL | Edition, availability, ... | Examination material | Language |
| Book | Response Surface Methodology | Myers, R.H. & Montgomery, D.C. | English | ||||
| Other online content | Home page | English | |||||
| Summary of lectures | Tilastollinen kokeiden suunnittelu ja otanta | Ruohonen, K. | Suomi | ||||
| Summary of lectures | Tilastollinen vastepintamallinnus | Piché, R. & Ruohonen, K. | Suomi |
Prerequisites
| Course | Mandatory/Advisable | Description |
| MAT-31096 Matrix Algebra 1 | Advisable |
Prerequisite relations (Requires logging in to POP)
Correspondence of content
| Course | Corresponds course | Description |
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Additional information
This is a self-study course.
Suitable for postgraduate studies
More precise information per implementation
| Implementation | Description | Methods of instruction | Implementation |