Statistical programming
1. |
Subject title |
Statistical programming Статистичко прoграмирање |
|||||||||||||||||||||||
2. |
Code |
m23_s_054 |
|||||||||||||||||||||||
3. |
Study program |
Cloud Computing, IT management, Bioinformatics, Security, Cryptography and Coding, Еducation with ICT, Eco-informatics, Inteligent Systems, Internet Technologies and cyber security, Computer Science, Statistics and Data Analytics, Software for embedded systems, Software Engineering, Cloud Computing, IT management, Bioinformatics, Security, Cryptography and Coding, Software Engineering, Statistics and Data Analytics, Data science in computer science and engineering, |
|||||||||||||||||||||||
4. |
Organizer of the study program (unit, institute, department, division) |
Faculty of Information Sciences and Computer Engineering |
|||||||||||||||||||||||
5. |
Study cycle (first, second, third) |
Втор циклус |
|||||||||||||||||||||||
6. |
Academic year / semester 5 / Летен |
7. Number of ECTS credits 6.0 |
|||||||||||||||||||||||
8. |
Instructor |
проф. д-р Кире Триводалиев проф. д-р Марија Михова |
|||||||||||||||||||||||
9. |
Prerequisites for enrollment |
|
|||||||||||||||||||||||
10. |
Subject goals and competencies: The course includes expanded use of a statistical programming language of choice (R and/or Python) and aims to get the students and use of such languages, with a special focus on statistical programming in the selected language.
|
||||||||||||||||||||||||
11. |
Subject content: Basic commands in r and python (arithmetic, logical and vectors operations; simulating random variables) Data structures and data work. Graphs in r (parcels, lines and dots, legends) Functions and Scripts (Simple Functions, For / While Cycles, If / IFELSE CONDITIONAL CONSTRUCTIONS) Quick cycles and effective programming (vector arithmetic, vectors versus functions, are apply/ mapply) Computer Intensive Techniques (Simulation Techniques, Random Tests Monte Carlo Integration, Bootstraping, Gibs Sampling) |
||||||||||||||||||||||||
12. |
Learning methods: NULL |
||||||||||||||||||||||||
13. |
Total available time fund |
6.0 ECTS x 30 hours = 180 hours |
|||||||||||||||||||||||
14. |
Time distribution |
60 + 0 + 30 + 60 + 30 = 180 hours
|
|||||||||||||||||||||||
15. |
Forms of teaching activities |
15.1. |
Lectures - theoretical teaching |
60 hours |
|||||||||||||||||||||
15.2. |
Exercises (laboratory, classroom), seminars, team work |
0 hours |
|||||||||||||||||||||||
16. |
Other forms of activities |
16.1. |
Project tasks |
60 hours
|
|||||||||||||||||||||
16.2. |
Independent tasks |
30 hours |
|||||||||||||||||||||||
16.3. |
Homework |
30 hours |
|||||||||||||||||||||||
17. |
Grading method |
||||||||||||||||||||||||
17.1. |
Tests |
0 points |
|||||||||||||||||||||||
17.2. |
Seminar work / project (presentation: written and oral) |
60 points |
|||||||||||||||||||||||
17.3. |
Activities and learning |
0 points |
|||||||||||||||||||||||
17.4. |
Final exam |
0 points |
|||||||||||||||||||||||
18. |
Grading criteria (points / grade) |
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. |
Condition for signature and taking final exam |
NULL |
|||||||||||||||||||||||
20. |
Language of instruction |
македонски |
|||||||||||||||||||||||
|
21. |
Quality assurance method |
|
|||||||||||||||||||||||
22. |
Literature |
||||||||||||||||||||||||
22.1. |
Mandatory literature |
||||||||||||||||||||||||
|
|||||||||||||||||||||||||
|
22.2. |
Additional literature |
|
|||||||||||||||||||||||