Universität Wien FIND

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220050 SE SE Advanced Data Analysis 2 (2021S)

Continuous assessment of course work
MIXED

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 30 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

Die LV ist als Hybride-Lehre geplant!

Thursday 11.03. 11:30 - 13:00 Hybride Lehre
Seminarraum 4, Währinger Straße 29 1.UG
Thursday 18.03. 11:30 - 13:00 Hybride Lehre
Seminarraum 4, Währinger Straße 29 1.UG
Thursday 25.03. 11:30 - 13:00 Hybride Lehre
Seminarraum 4, Währinger Straße 29 1.UG
Thursday 15.04. 11:30 - 13:00 Hybride Lehre
Seminarraum 4, Währinger Straße 29 1.UG
Thursday 22.04. 11:30 - 13:00 Hybride Lehre
Seminarraum 4, Währinger Straße 29 1.UG
Thursday 29.04. 11:30 - 13:00 Hybride Lehre
Seminarraum 4, Währinger Straße 29 1.UG
Thursday 06.05. 11:30 - 13:00 Hybride Lehre
Seminarraum 4, Währinger Straße 29 1.UG
Thursday 20.05. 11:30 - 13:00 Hybride Lehre
Seminarraum 4, Währinger Straße 29 1.UG
Thursday 27.05. 11:30 - 13:00 Hybride Lehre
Seminarraum 4, Währinger Straße 29 1.UG
Thursday 10.06. 11:30 - 13:00 Hybride Lehre
Seminarraum 4, Währinger Straße 29 1.UG
Thursday 17.06. 11:30 - 13:00 Hybride Lehre
Seminarraum 4, Währinger Straße 29 1.UG
Thursday 24.06. 11:30 - 13:00 Hybride Lehre
Seminarraum 4, Währinger Straße 29 1.UG

Information

Aims, contents and method of the course

This is a data analysis seminar focused on the study and application of principles of time series analysis.

Part of the course will be spent talking about the specificity of time series data and the main approaches to time series analysis, focusing on some of the techniques to analyze this particular type of data. Computer applications will focus on R statistical language. A moderate knowledge of R and R programming is useful but not necessary, since the course includes a hands-on training on the functions necessary to conduct the analyses described during the lessons.

By the end of this course participants will be able to:
- describe the specificities of time series data and the fundamental concepts of time series analysis;
- interpret common types of analysis of time series;
- visualize and conduct time series analysis with R

Assessment and permitted materials

Assignments distributed during the course, dealing with demonstrating the understanding of key concepts (30%).
A final data analysis project where participants will apply the knowledge and techniques learned during the course (70%).

Minimum requirements and assessment criteria

Ongoing in-class participation is required. The assignments and the final project will be evaluated based on their theoretical and methodological accuracy.

Examination topics

Theoretical knowledge and practical skills will be conveyed in the lectures, tutorials, and required readings.

Reading list

The literature will be made available to participants during the course

Association in the course directory

Last modified: We 21.04.2021 11:26