| 1. | Course Title | Probability Theory and Statistics | |||||||||||
| 2. | Code | 4ФЕИТ08001 | |||||||||||
| 3. | Study program | 13-PMA | |||||||||||
| 4. | Organizer of the study program (unit, institute, department) | Faculty of Electrical Engineering and Information Technologies | |||||||||||
| 5. | Degree (first, second, third cycle) | Second cycle | |||||||||||
| 6. | Academic year/semester | I/1 | 7. | Number of ECTS credits | 6.00 | ||||||||
| 8. | Lecturer | Dr Katerina Hadji Velkova – Saneva | |||||||||||
| 9. | Course Prerequisites | ||||||||||||
| 10. | Course Goals (acquired competencies):
Ability to communicate in writing, problem solving, ability to analyze and synthesize, problem solving, critical ability and ability to learn in the fields of probability and statistics. |
||||||||||||
| 11. | Course Syllabus:
Probability. Random events. Conditional probability. Independence of events. Bayes theorem. Random variables. Numerous characteristics of random variables. Random vectors. Common distribution functions. Covariance and Correlation. Functions of random variables. Generating functions. Limit theorems. Basic concepts of random processes. Characterization and classification of random processes. Introduction to Statistics. A random sample. Descriptive statistics. Graphical representation of data. Assessment theory. Point estimation methods: method of moments, maximum likelihood method, Bayesian estimation. Confidence intervals. Decision Theory. Hypothesis testing. Using software for statistical data processing. |
||||||||||||
| 12. | Learning methods:
Observation and experiment, comparison, analysis and synthesis, generalization, systematization and abstraction. |
||||||||||||
| 13. | Total number of course hours | 180 | |||||||||||
| 14. | Distribution of course hours | 3 + 3 | |||||||||||
| 15. | Forms of teaching | 15.1 | Lectures-theoretical teaching | 45 hours | |||||||||
| 15.2 | Exercises (laboratory, practice classes), seminars, teamwork | 45 hours | |||||||||||
| 16. | Other course activities | 16.1 | Projects, seminar papers | 30 hours | |||||||||
| 16.2 | Individual tasks | 30 hours | |||||||||||
| 16.3 | Homework and self-learning | 30 hours | |||||||||||
| 17. | Grading | ||||||||||||
| 17.1 | Exams | points | |||||||||||
| 17.2 | Seminar work/project (presentation: written and oral) | points | |||||||||||
| 17.3. | Activity and participation | points | |||||||||||
| 17.4. | Final exam | 100 points | |||||||||||
| 18. | Grading criteria (points) | up to 50 points | 5 (five) (F) | ||||||||||
| from 51 to 60 points | 6 (six) (E) | ||||||||||||
| from 61 to 70 points | 7 (seven) (D) | ||||||||||||
| from 71 to 80 points | 8 (eight) (C) | ||||||||||||
| from 81 to 90 points | 9 (nine) (B) | ||||||||||||
| from 91 to 100 points | 10 (ten) (A) | ||||||||||||
| 19. | Conditions for acquiring teacher’s signature and for taking final exam | none | |||||||||||
| 20. | Forms of assessment | Oral and written | |||||||||||
| 21. | Language | Macedonian and English | |||||||||||
| 22. | Method of monitoring of teaching quality | Self-evaluation | |||||||||||
| 23. | Literature | ||||||||||||
| 23.1. | Required Literature | ||||||||||||
| No. | Author | Title | Publisher | Year | |||||||||
| 1. | Ј. P. Marques de Sa | Applied statistics using SPSS, STATISTICA, MATLAB and R | Springer | 2007 | |||||||||
| 2. | Анета Бучковска, Катерина Хаџи Велкова Санева, Сања Атанасова | Вовед во веројатност за инженери | ФЕИТ | 2017 | |||||||||
| 23.2. | Additional Literature | ||||||||||||
| No. | Author | Title | Publisher | Year | |||||||||
| 1. | G.Jay Kerns | Introduction to Probability and Statistics Using R | Cran.r-project.org ISBN: 978-0-557-24979-4 | 2011 | |||||||||
| 2. | Venkatarama Krishnan | Probability and Random Processes | Wiley | 2006 | |||||||||
