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180112 VO+UE Tools in Cognitive Science II: Basic Statistics for Cognitive Scientists (2018S)
Continuous assessment of course work
Labels
1.Termin (Vorbesprechung): Mo 5. März 2018, 9:00 - 11:00
HS 2i d. Inst. f. Philosophie, NIG, 2. StockWeitere Termine werden bei der Vorbesprechung bekannt gegeben!
HS 2i d. Inst. f. Philosophie, NIG, 2. StockWeitere Termine werden bei der Vorbesprechung bekannt gegeben!
Registration/Deregistration
- Registration is open from Th 15.02.2018 00:00 to Th 08.03.2018 23:59
- Deregistration possible until Sa 31.03.2018 23:59
Details
max. 25 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
Thursday
08.03.
10:30 - 12:00
Hörsaal 1, UZA 1, Biozentrum Althanstraße 14, 1.008A EG
Thursday
08.03.
12:00 - 13:30
EDV-Raum 2 Ökologie Biozentrum Z1.023 EG
Thursday
15.03.
10:30 - 12:00
Übungsraum 2, UZA 1, Biozentrum Althanstraße 14, Morphologie Z2.010 1.OG
Thursday
15.03.
12:00 - 13:30
EDV-Raum 2 Ökologie Biozentrum Z1.023 EG
Thursday
22.03.
10:30 - 12:00
Hörsaal 1, UZA 1, Biozentrum Althanstraße 14, 1.008A EG
Thursday
22.03.
12:00 - 13:30
EDV-Raum 2 Ökologie Biozentrum Z1.023 EG
Thursday
12.04.
10:30 - 12:00
Hörsaal 1, UZA 1, Biozentrum Althanstraße 14, 1.008A EG
Thursday
12.04.
12:00 - 13:30
EDV-Raum 2 Ökologie Biozentrum Z1.023 EG
Thursday
19.04.
10:30 - 12:00
Hörsaal 1, UZA 1, Biozentrum Althanstraße 14, 1.008A EG
Thursday
19.04.
12:00 - 13:30
EDV-Raum 2 Ökologie Biozentrum Z1.023 EG
Thursday
26.04.
10:30 - 12:00
Hörsaal 1, UZA 1, Biozentrum Althanstraße 14, 1.008A EG
Thursday
26.04.
12:00 - 13:30
EDV-Raum 2 Ökologie Biozentrum Z1.023 EG
Thursday
03.05.
10:30 - 12:00
Hörsaal 1, UZA 1, Biozentrum Althanstraße 14, 1.008A EG
Thursday
03.05.
12:00 - 13:30
EDV-Raum 2 Ökologie Biozentrum Z1.023 EG
Thursday
17.05.
12:00 - 13:30
EDV-Raum 2 Ökologie Biozentrum Z1.023 EG
Thursday
24.05.
10:30 - 12:00
Hörsaal 1, UZA 1, Biozentrum Althanstraße 14, 1.008A EG
Thursday
24.05.
12:00 - 13:30
EDV-Raum 2 Ökologie Biozentrum Z1.023 EG
Thursday
07.06.
10:30 - 12:00
Hörsaal 1, UZA 1, Biozentrum Althanstraße 14, 1.008A EG
Thursday
07.06.
12:00 - 13:30
EDV-Raum 2 Ökologie Biozentrum Z1.023 EG
Thursday
14.06.
10:30 - 12:00
Hörsaal 1, UZA 1, Biozentrum Althanstraße 14, 1.008A EG
Thursday
14.06.
12:00 - 13:30
EDV-Raum 2 Ökologie Biozentrum Z1.023 EG
Thursday
21.06.
10:30 - 12:00
Hörsaal 1, UZA 1, Biozentrum Althanstraße 14, 1.008A EG
Thursday
21.06.
12:00 - 13:30
EDV-Raum 2 Ökologie Biozentrum Z1.023 EG
Thursday
28.06.
12:00 - 13:30
EDV-Raum 2 Ökologie Biozentrum Z1.023 EG
Information
Aims, contents and method of the course
Assessment and permitted materials
The finale grade consists of an exam, active participation and practical work during the course, personal attendance and homework exercises.
Minimum requirements and assessment criteria
Minimum requirements for passing the course:
- Active participation in practical part (you may miss max. 2 sessions [please inform the instructor ahead of time]) (25%)
- Homework assignements during the practical part (you can miss out one assignement, but should try to supply asap) (25%)
- Final exam (50%)
The final grade consists of a combination of the above mentioned evaluation criteria (percentage in parentheses)
- Active participation in practical part (you may miss max. 2 sessions [please inform the instructor ahead of time]) (25%)
- Homework assignements during the practical part (you can miss out one assignement, but should try to supply asap) (25%)
- Final exam (50%)
The final grade consists of a combination of the above mentioned evaluation criteria (percentage in parentheses)
Examination topics
Reading list
Association in the course directory
Last modified: Mo 07.09.2020 15:36
The practical part should foster the understanding of theoretical concepts via basic examples from different research fields (mainly biology related research topics). We will try to "produce" our data, visualize and analyze them.
Expectations and learning outcomes from the practical part:
- overview of the plethora of statistcal methodologies
- use of different statistical programs (SPSS, R, R Studio)
- Scientific visualization in practice
- Applied scientific reasoning and critical discussion of their statistical methodologies for scientific research