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Optimization Methods in Chemistry

General data

Course ID: 1200-2SPEC52M
Erasmus code / ISCED: 13.3 Kod klasyfikacyjny przedmiotu składa się z trzech do pięciu cyfr, przy czym trzy pierwsze oznaczają klasyfikację dziedziny wg. Listy kodów dziedzin obowiązującej w programie Socrates/Erasmus, czwarta (dotąd na ogół 0) – ewentualne uszczegółowienie informacji o dyscyplinie, piąta – stopień zaawansowania przedmiotu ustalony na podstawie roku studiów, dla którego przedmiot jest przeznaczony. / (0531) Chemistry The ISCED (International Standard Classification of Education) code has been designed by UNESCO.
Course title: Optimization Methods in Chemistry
Name in Polish: Metody optymalizacji w chemii
Organizational unit: Faculty of Chemistry
Course groups: (in Polish) Przedmioty do wyboru w semestrze 3M (S2-PRK-CHM)
(in Polish) Wykłady specjalizacyjne w semestrze 2M
ECTS credit allocation (and other scores): 3.00 Basic information on ECTS credits allocation principles:
  • the annual hourly workload of the student’s work required to achieve the expected learning outcomes for a given stage is 1500-1800h, corresponding to 60 ECTS;
  • the student’s weekly hourly workload is 45 h;
  • 1 ECTS point corresponds to 25-30 hours of student work needed to achieve the assumed learning outcomes;
  • weekly student workload necessary to achieve the assumed learning outcomes allows to obtain 1.5 ECTS;
  • work required to pass the course, which has been assigned 3 ECTS, constitutes 10% of the semester student load.
Language: Polish
Type of course:

obligatory courses
Prerequisites (description):

Introductory course on statistical methods.
Mode:

Classroom
Short description:

Introduction to basic methods used in optimization.
Full description:

1. Conception of experiment, experimental error from statistical point of view, statistical estimating, maximum likelihood function.

2. Maximum likelihood function in the case of experiment with errors subjected to normal distribution of errors, methods derived from maximum likelihood method, MML (Multiresponse Maximum Likelihood) method, weighed (methods of error propagation) method of least squares, simplified method of least squares (mostly used due to its simplicity and, probably, due to ignorance of users).

3. Regression and correlation. Methods of parameters fitting in models based on statistical testing.

4. Variance analysis, statistical tests.

5. Statistical tools implemented in MSExcel, use of built-in VBA programming language.
Bibliography:

1. Czermiński J., Iwasiewicz, A., Paszek, Z., Sikorski, A, Metody statystyczne dla chemików, PWN, Warszawa 1992.

2. Korzyński Mieczysław, Metodyka eksperymentu. Planowanie, realizacja i statystyczne opracowanie wyników eksperymentów technologicznych, WNT, 2006

3. Koronacki Jacek, Mielniczuk Jan, Statystyka dla studentów kierunków technicznych i przyrodniczych, WNT, 2006.
Learning outcomes:

Student uses practical knowledge of application of maximum likelihood function for correct developing of optimization criteria. Practically uses of built-in in the MSExcel application programming language VBA (Visual Basic for Application).
Assessment methods and assessment criteria:

Student's activities during practical training and, optionally, short test with grading when needed.

The maximum number of absences should not exceed 20% of the total class time.
Practical placement:

not concern

Classes in period "Summer semester 2023/24" (in progress)

Time span: 2024-02-19 - 2024-06-16
Selected timetable range:
Navigate to timetable
Type of class:
Specialised lecture, 30 hours, 30 places more information
Coordinators: Paweł Oracz
Group instructors: Paweł Oracz
Students list: (inaccessible to you)
Examination: Examination
Course descriptions are protected by copyright.
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