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| YZM 102 | Probability and Statistics | 2+1+0 | ECTS:3 | | Year / Semester | Spring Semester | | Level of Course | First Cycle | | Status | Compulsory | | Department | DEPARTMENT of SOFTWARE ENGINEERING | | Prerequisites and co-requisites | None | | Mode of Delivery | Face to face, Lab work | | Contact Hours | 14 weeks - 2 hours of lectures and 1 hour of practicals per week | | Lecturer | -- | | Co-Lecturer | | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | To give basic information about the concepts and theory of probability. |
| Learning Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | LO - 1 : | knows the basic concepts of probability | 1,2,5,6,10,12,13 | 1,3 | | LO - 2 : | knows the probability distributions and models | 1,2,5,6,10,12,13 | 1,3 | | LO - 3 : | can make probability based analysis and analysis of some of the problems in computer engineering | 1,2,5,6,10,12,13 | 1,3 | | LO - 4 : | knows computer engineering applications of probability | 1,2,5,6,10,12,13 | 1,3 | | LO - 5 : | can use SPSS effectively | 1,2,5,6,10,12,13 | 3,4 | | 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 | | |
| Axiomatic approach to probability, probability axioms, conditional probability and statistical independence, independent variables, probability distributions, means, and standard deviations, variance, shared variables, Binomial, Gaussian, Uniform, Rayleigh, Rician, Exponential, Gamma distributions and their models, characteristics. Functions, probability functions, conversion techniques, multivariate probability distributions, the general input processes, correlation functions and their applications |
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Fundamentals of probability, probability axiomatic approach | | | Week 2 | The concept of cluster and clusters | | | Week 3 | Conditional probability, compound events, examples | | | Week 4 | Statistical indepence and Bayes theorem | | | Week 5 | Random variables, probability density functions | | | Week 6 | Probability distribution functions | | | Week 7 | Probability distribution models, binomial distribution | | | Week 8 | Gaussian, exponential and rayleigh distribution | | | Week 9 | Midterm Exam 1 | | | Week 10 | Poisson distribution and examples | | | Week 11 | Multiple random variables and functions | | | Week 12 | Midterm Exam 2 | | | Week 13 | Multiple distribution functions, relationships, and covariance, correlation coefficient and regression analysis | | | Week 14 | random processes | | | Week 15 | Probability applications to engineering problems | | | Week 16 | Final Exam | | | |
| 1 | Uygulamalı İstatistik ? I ve II, Alim Işık, Beta Basım Yayım, 2006. | | | |
| 1 | Ziemer R.E, 1997; Elements of Engineering Probability and Statistics, Prentice-Hall, USA | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 9
12 | | 1
1 | 40 | | Laboratory exam | 9
12 | | 1
1 | 10 | | End-of-term exam | 16 | | 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 | 13 | 39 | | Sınıf dışı çalışma | 1 | 10 | 10 | | Arasınav için hazırlık | 2 | 5 | 10 | | Arasınav | 2 | 2 | 4 | | Uygulama | 1 | 13 | 13 | | Ödev | 2 | 4 | 8 | | Kısa sınav | 1 | 2 | 2 | | Dönem sonu sınavı için hazırlık | 2 | 5 | 10 | | Dönem sonu sınavı | 2 | 1 | 2 | | Diğer 1 | 3 | 5 | 15 | | Total work load | | | 113 |
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