PřF:C6140 Optimization and Evaluation of - Course Information
C6140 Optimization and Evaluation of Analytical Methods
Faculty of ScienceSpring 2020
- Extent and Intensity
- 2/0/0. 2 credit(s) (fasci plus compl plus > 4). Recommended Type of Completion: zk (examination). Other types of completion: k (colloquium).
- Teacher(s)
- RNDr. Marta Farková, CSc. (lecturer)
- Guaranteed by
- RNDr. Marta Farková, CSc.
Department of Chemistry – Chemistry Section – Faculty of Science
Supplier department: Department of Chemistry – Chemistry Section – Faculty of Science - Timetable
- Mon 13:00–14:50 B09/316
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Analytical Chemistry (programme PřF, M-CH)
- Analytical Chemistry (programme PřF, N-CH)
- Inorganic Chemistry (programme PřF, M-CH)
- Biochemistry (programme PřF, M-CH)
- Physical Chemistry (programme PřF, M-CH)
- Chemistry (programme PřF, M-CH)
- Environmental Chemistry (programme PřF, M-CH)
- Macromolecular Chemistry (programme PřF, M-CH)
- Organic Chemistry (programme PřF, M-CH)
- Upper Secondary School Teacher Training in Chemistry (programme PřF, M-CH)
- Upper Secondary School Teacher Training in Chemistry (programme PřF, M-SS)
- Course objectives
- In this course, students will be introduced into the mathematical models, they will learn how to determine their parameters, to do linear regression, to do general regression and to optimize analytical methods.
- Learning outcomes
- At the end of the course student will be able to determine mathematical models and their parameters; to do linear regression; to do general regression; to optimize analytical methods.
- Syllabus
- 1. Mathematical model. 2. Linear regression. 3. Transformation to linear regression. 4. Application of statistical weights in linear regression. 5. Multiple linear regression. 6. Polynomial regression, splines. 7. Methods of general regression - single-variable functions. 8. Methods of general regression - multi-variable functions. 9. Method optimization.
- Literature
- PYTELA, Oldřich. Optimalizace. 1. vyd. Pardubice: Vysoká škola chemicko-technologická, 1982, 115 s. info
- Teaching methods
- Type of education: lectures, class discussion, the practical exercises are solved on PC
- Assessment methods
- Type of exam: written and oral exam, individual work. 70% of correct answers is needed to pass.
- Language of instruction
- Czech
- Further Comments
- Study Materials
The course is taught annually.
- Enrolment Statistics (Spring 2020, recent)
- Permalink: https://is.muni.cz/course/sci/spring2020/C6140