SubjectsSubjects(version: 962)
Course, academic year 2024/2025
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Econometric Project Seminar - NMEK551
Title: Ekonometrický projektový seminář
Guaranteed by: Department of Probability and Mathematical Statistics (32-KPMS)
Faculty: Faculty of Mathematics and Physics
Actual: from 2023
Semester: winter
E-Credits: 5
Hours per week, examination: winter s.:0/2, C [HT]
Capacity: unlimited
Min. number of students: unlimited
4EU+: no
Virtual mobility / capacity: no
State of the course: not taught
Language: Czech
Teaching methods: full-time
Teaching methods: full-time
Guarantor: doc. RNDr. Zdeněk Hlávka, Ph.D.
doc. RNDr. Ing. Miloš Kopa, Ph.D.
Class: M Mgr. PMSE
M Mgr. PMSE > Povinně volitelné
Classification: Mathematics > Math. Econ. and Econometrics
Pre-requisite : NMEK432, NMEK450
Is incompatible with: NMEK521
Is interchangeable with: NEKN005
Annotation -
Given a real-life problem presentation and data, the teams of students are supposed to suggest an approach to find a tractable way to the problem solution and to write a report. Limited number of students.
Last update: T_KPMS (10.05.2013)
Aim of the course -

The objective is getting experience in team work on a real problem including data preparation, making out the final report and defending it.

Last update: T_KPMS (10.05.2013)
Course completion requirements -

Conditions for successful completion of the seminar: attendance at checkpoints, submission of high-quality work at the given deadline, preparation of the assigned review and active participation in the final presentations. The nature of the credit (zápočet) does not allow it to be repeated. Students in non-degree programme cannot enrol in this seminar.

Last update: Hlávka Zdeněk, doc. RNDr., Ph.D. (19.01.2023)
Literature -

According to problems to be solved.

Last update: T_KPMS (29.04.2015)
Teaching methods -

Seminar: elaboration and presentation of a real project, usually with an economic focus. The faculty computing cluster can be used for more demanding data analyses and processing of large data sets.

Last update: Hlávka Zdeněk, doc. RNDr., Ph.D. (19.01.2023)
Entry requirements -

very good knowledge of linear regression, time series analysis, econometrics, and optimization

Last update: Hlávka Zdeněk, doc. RNDr., Ph.D. (25.05.2018)
 
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