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| BSP 104 | Statistics | 3+0+0 | ECTS:5 | | Year / Semester | Spring Semester | | Level of Course | Short Cycle | | Status | Compulsory | | Department | | | Prerequisites and co-requisites | None | | Mode of Delivery | Face to face | | Contact Hours | 14 weeks - 3 hours of lectures per week | | Lecturer | -- | | Co-Lecturer | None | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | The objective of this course is to help students by teaching statistical inference methods used in decision making during professional life and to help them develop their scientific thinking. |
| Learning Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | LO - 1 : | Knowledge they had gained experience in business life and mathematical data analysis be able to do. | 1,3,8,9 | 1 | | LO - 2 : | Keeping the data they needed to obtain statistical evaluations, can have healthy consequences.
| 1,3,8,9 | 1 | | LO - 3 : | Ability to think analytically and can win | 1,3,8,9 | 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), LO : Learning Outcome | | |
| Measures of central propensity: Arithmetic mean, median, mode, harmonic mean, geometric meanMeasures of distribution, skewness and kurtosis: Range, standard deviation, skewness and kurtosis measures. Indexes: Simple index and composite indexPossibility theory: Addition rule, multiplication rule, conditional possibility, aggregate possibility and the Bayes theorem. |
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Statistics of the definition, purpose, scope, and some basic concepts
| | | Week 2 | Data collection, processing and editing. Graphic presentation of data with | | | Week 3 | Measures of central tendency: Mean, median, mode, average, kantiller. | | | Week 4 | Measures of central tendency: Mean, median, mode, average, kantiller. | | | Week 5 | Dispersion, skew and kurtosis Measurements: Change range, average deviation, standard deviation
| | | Week 6 | Dispersion, skew and kurtosis dimensions: Exchange coefficient and coefficient of skew
| | | Week 7 | Dispersion, skew and kurtosis Measurements: Moments
| | | Week 8 | Some basic concepts, probability concepts, the basic features of probability, probability rules | | | Week 9 | Mid-term exam | | | Week 10 | Conditional probability
| | | Week 11 | Bayes theorem | | | Week 12 | Solutions to questions of probability and Bayes' theorem | | | Week 13 | Solutions to questions of probability and Bayes' theorem | | | Week 14 | Correlation analysis | | | Week 15 | Correlation analysis | | | Week 16 | End-of-term exam | | | |
| 1 | Köseoğlu, Yamak,Trabzon 2008 Uygulamalı istatistik | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 9 | 10/04/2013 | 0,70 | 50 | | End-of-term exam | 16 | 06/06/2013 | 0,50 | 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 | 5 | 13 | 65 | | Sınıf dışı çalışma | 4 | 13 | 52 | | Arasınav için hazırlık | 15 | 1 | 15 | | Arasınav | 2 | 1 | 2 | | Dönem sonu sınavı için hazırlık | 15 | 1 | 15 | | Dönem sonu sınavı | 1 | 1 | 1 | | Total work load | | | 150 |
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