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| MGKT1020 | Mathematical Applications in Food Analysis | 2+0+0 | ECTS:4 | | Year / Semester | Spring Semester | | Level of Course | Short Cycle | | Status | Compulsory | | Department | DEPARTMENT of FOOD PROCESSING | | Prerequisites and co-requisites | None | | Mode of Delivery | | | Contact Hours | 14 weeks - 2 hours of lectures per week | | Lecturer | Dr. Öğr. Üyesi Gülsüm Merve BOYRACI | | Co-Lecturer | Asst. Prof. Esra ULUSOY | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | To develop students' mathematical skills in solving technical problems encountered in food production, food processing and quality control processes.
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| Learning Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | LO - 1 : | Be able to define basic statistical and probability concepts and rules. | 1 - 6 | 1,3, | | LO - 2 : | Summarize data and interpret graphics. | 1 - 6 | 1,3, | | LO - 3 : | Be able to make and interpret simple calculations for professional accounts. | 1 - 6 | 1,3, | | 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), LO : Learning Outcome | | |
| The correct spelling and expression of mathematical concepts that they can use in the professional field are explained. It transfers the transformations of the units used in the field of food to each other. Basic statistical calculations include calculation of mean, standard deviation values, evaluation of data, creation of calibration graphs and finding results from equations, basic analysis calculations used in foods. |
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Basic calculation concepts (unit conversions, basic arithmetic, unit conversion) | | | Week 2 | Introduction to Statistics The role and meaning of statistics | | | Week 3 | Basic statistical terms, data types, organization and classification of data | | | Week 4 | Statistical representations of data, graphical representations | | | Week 5 | Descriptive Statistics Center Trend Measures | | | Week 6 | Descriptive Statistics Deviation Criteria from the Mean | | | Week 7 | Creation of standard calibration curves | | | Week 8 | Moisture and Total Dry Matter Analysis Calculations in Foods
| | | Week 9 | Mid-Term Exam | | | Week 10 | Calculation of total ash analysis in foods
| | | Week 11 | Total acidity calculations in foods | | | Week 12 | Total Salt Calculations in Foods
| | | Week 13 | Mass balance calculations in food production | | | Week 14 | Efficiency Calculation in Food Production | | | Week 15 | Food Additives Calculation | | | Week 16 | End-term Exam | | | |
| 1 | HECER, C., ULUSOY, B. 2015; Gıda Analizleri, Dora Yayınları, Bursa
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| 1 | Öğretim elemanı ders notları | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 9 | | 1 | 50 | | End-of-term exam | 16 | | 1 | 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 | 2 | 14 | 28 | | Sınıf dışı çalışma | 2 | 14 | 28 | | Arasınav için hazırlık | 2 | 8 | 16 | | Arasınav | 1 | 1 | 1 | | Ödev | 1 | 8 | 8 | | Dönem sonu sınavı için hazırlık | 2 | 9 | 18 | | Dönem sonu sınavı | 1 | 1 | 1 | | Total work load | | | 100 |
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