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| EAK6016 | Experimental Design in Analytical Method Development | 3+0+0 | ECTS:7.5 | | Year / Semester | Spring Semester | | Level of Course | Third Cycle | | Status | Elective | | Department | ANALYTICAL CHEMISTRY IN PHARMACY | | Prerequisites and co-requisites | None | | Mode of Delivery | | | Contact Hours | 14 weeks - 3 hours of lectures per week | | Lecturer | Dr. Öğr. Üyesi Sercan YILDIRIM | | Co-Lecturer | | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | This course aims to teach experimental design practices that allow detailed analytical method optimization with a small number of experiments and to encourage the use of this approach by students. |
| Programme Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | PO - 1 : | Learns basic statistics for experimental design | 5,7,8,12 | 1, | | PO - 2 : | Gains a new perspective in the optimization of analytical processes | 5,7,8,12 | 1, | | PO - 3 : | Gains the ability to make detailed method optimization by performing a small number of experiments | 5,7,8,12 | 1, | | PO - 4 : | Understand that experimental design can be used not only in analytical chemistry but also in all areas where numerical parameters need to be optimized and incorporate experimental design into optimization processes in these fields | 5,7,8,12 | 1, | | CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), PO : Learning Outcome | | |
| One of the most important steps in analytical processes is method optimization, which is often carried out one parameter at a time. On the other hand, this approach requires a large number of experiments and ignores the factor interactions affecting the result. In this course, students will be introduced to methods for determining the factors affecting an outcome by performing a small number of experiments by experimental design and optimizing them using chemometric tools. The main objective of the course is to provide students with the ability to apply the experimental design approach to the optimization of any numerical result.
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Basic statistics for the design of experiments | | | Week 2 | Simple comparative experiments | | | Week 3 | The keys to good design of experiments | | | Week 4 | Two-level factorial design | | | Week 5 | Dealing with nonnormality via response transformations | | | Week 6 | Fractional factorials | | | Week 7 | General multilevel categoric factorials | | | Week 8 | Response surface methods | | | Week 9 | Midterm exam | | | Week 10 | Strategy of experimentation: Role for response surface methodology | | | Week 11 | Central composite design | | | Week 12 | The Box?Behnken design | | | Week 13 | Finding optimum spot for multiple responses | | | Week 14 | Applications of experimental design in analytical procedures | | | Week 15 | Applications of experimental design in analytical procedures | | | Week 16 | Final exam | | | |
| 1 | Mark J. Anderson, Patrick J. Whitcomb, DOE Simplified: Practical Tools for Effective Experimentation, 3rd Edition, CRC Press, 2007, 13: 978-1-4987-3090-7 | | | 2 | Mark J. Anderson, Patrick J. Whitcomb, RSM Simplified: Optimizing Processes Using Response Surface Methods for Design of Experiments 2nd Edition, CRC Press, 2017, 13: 978-1-4987-4598-7 | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 9 | 15/04/2024 | 2 | 30 | | In-term studies (second mid-term exam) | 15 | 30/05/2024 | 1 | 20 | | End-of-term exam | 16 | 03/06/2024 | 2 | 50 | | |
| Student Work Load and its Distribution | | Type of work | Duration (hours pw) | No of weeks / Number of activity | Hours in total per term | | Yüz yüze eğitim | 3 | 14 | 42 | | Sınıf dışı çalışma | 5 | 14 | 70 | | Arasınav için hazırlık | 3 | 7 | 21 | | Arasınav | 2 | 1 | 2 | | Ödev | 6 | 4 | 24 | | Dönem sonu sınavı için hazırlık | 4 | 7 | 28 | | Dönem sonu sınavı | 2 | 1 | 2 | | Total work load | | | 189 |
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