All materials required for this course are available under E course Computational Statistics on Merlin: link.
Link to the notices web page: https://www.pmf.unizg.hr/math/predmet/racsta
Code: 
61532 
ECTS:  5.0 
Lecturers in charge: 
doc. dr. sc.
Snježana Lubura Strunjak

Lecturers: 
doc. dr. sc.
Snježana Lubura Strunjak
 Exercises 
English level:
1,0,0 
All teaching activities will be held in Croatian. However, foreign students in mixed groups will have the opportunity to attend additional office hours with the lecturer and teaching assistants in English to help master the course materials. Additionally, the lecturer will refer foreign students to the corresponding literature in English, as well as give them the possibility of taking the associated exams in English. 
Load:  


Description:  
COURSE AIMS AND OBJECTIVES: This course aims to demonstrate how computer intensive methods can be used to extend the inference methods to those situations where classical approaches fall short. Additionally, students will be exposed to Monte Carlo, resampling, and selected statistical learning methods. The emphasis will be on algorithms, software tools, and practical applications from pharmaceutical, finance, and engineering areas. 

Literature:  


Prerequisit for:  
Enrollment : 
3. semester 
Izborni predmet 3, 4, 5, 6  Regular study  Computer Science and Mathematics 
4. semester Not active 
Izborni predmet 3, 4, 5, 6  Regular study  Computer Science and Mathematics 
All materials required for this course are available under E course Computational Statistics on Merlin: link.
Link to the notices web page: https://www.pmf.unizg.hr/math/predmet/racsta