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| EKO 307 | Probability | 3+0+0 | ECTS:4 | | Year / Semester | Fall Semester | | Level of Course | First Cycle | | Status | Compulsory | | Department | DEPARTMENT of ECONOMETRICS | | 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 purpose of the course is to provide knowledge of probability theory, statistical inference and stationary processes and to give an understanding of the application of these to real technical problems. |
| Learning Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | LO - 1 : | get some basic probabilityconcepts about economics formation. | 1,2,3,4,5,6,7 | 1 | | LO - 2 : | apply basic probability problems to ecenomic | 1,2,3,4,5,6,7 | 1 | | LO - 3 : | apply different probability functions to economics models | 1,2,3,4,5,6,7 | 1 | | LO - 4 : | get some new probability techniques to apply problems in ecenomics | 1,2,3,4,5,6,7 | 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 | | |
| Sample space, laws of probability, independence and conditional probability, random variables, marginal, joint and conditional distributions, expected value and conditional expected value, discrete and continuous distributions, moment generating functions, law of large numbers and central limit theorem |
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Random variables | | | Week 2 | The mean, or expected value, of a random variable
Standart deviation of a random variable | | | Week 3 | Introduction to Theoritical Probability Distribution | | | Week 4 | The binomial probability distribution | | | Week 5 | table of binomial probabilities | | | Week 6 | Mean and standart deviation of a binomial distribution | | | Week 7 | The binomial formula applied to bayes'problems | | | Week 8 | The hypergeometric disribution | | | Week 9 | Mid-Term- Exam | | | Week 10 | mean and standart deviation of a hypergeometric disribution | | | Week 11 | The normal distribution | | | Week 12 | Areas under normal curve | | | Week 13 | Some practice problems utilizing the table of areas under the normal curve | | | Week 14 | Using the normal curve to approximate binomial probabilities | | | Week 15 | The poisson distribution, applying the poisson formula | | | Week 16 | End of term exam | | | |
| 1 | Lipschutz, Seymour (çeviri,H.Kutkuk Özgün),1996,Olasılık, Nobel yayınları; Ankara | | | |
| 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 | | Sınıf dışı çalışma | 3 | 14 | 42 | | Arasınav için hazırlık | 6 | 2 | 12 | | Arasınav | 1 | 1 | 1 | | Dönem sonu sınavı için hazırlık | 11 | 2 | 22 | | Dönem sonu sınavı | 1 | 1 | 1 | | Total work load | | | 78 |
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