300322 VU Biological Data: introduction to statistics and SPSS (2023W)
Continuous assessment of course work
Labels
ON-SITE
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).
- Registration is open from Th 07.09.2023 14:00 to Th 21.09.2023 18:00
- Deregistration possible until Su 15.10.2023 18:00
Details
max. 24 participants
Language: German
Lecturers
Classes (iCal) - next class is marked with N
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Monday
02.10.
15:00 - 18:30
Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1 - Tuesday 03.10. 16:45 - 19:15 Seminarraum 1.2, Biologie Djerassiplatz 1, 1.004, Ebene 1
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Monday
09.10.
15:00 - 18:30
Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1 - Tuesday 10.10. 16:45 - 19:15 Seminarraum 1.2, Biologie Djerassiplatz 1, 1.004, Ebene 1
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Monday
16.10.
15:00 - 18:30
Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1 - Tuesday 17.10. 16:45 - 19:15 Seminarraum 1.2, Biologie Djerassiplatz 1, 1.004, Ebene 1
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Monday
23.10.
15:00 - 18:30
Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1 - Tuesday 24.10. 16:45 - 19:15 Seminarraum 1.2, Biologie Djerassiplatz 1, 1.004, Ebene 1
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Monday
30.10.
15:00 - 18:30
Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1 - Tuesday 31.10. 16:45 - 19:15 Seminarraum 1.2, Biologie Djerassiplatz 1, 1.004, Ebene 1
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Monday
06.11.
15:00 - 18:30
Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1 - Tuesday 07.11. 16:45 - 19:15 Seminarraum 1.2, Biologie Djerassiplatz 1, 1.004, Ebene 1
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Monday
13.11.
15:00 - 18:30
Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1 - Tuesday 14.11. 16:45 - 19:15 Seminarraum 1.2, Biologie Djerassiplatz 1, 1.004, Ebene 1
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Monday
20.11.
15:00 - 18:30
Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1 - Tuesday 21.11. 16:45 - 19:15 Seminarraum 1.2, Biologie Djerassiplatz 1, 1.004, Ebene 1
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Monday
27.11.
15:00 - 18:30
Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1 - Tuesday 28.11. 16:45 - 19:15 Seminarraum 1.2, Biologie Djerassiplatz 1, 1.004, Ebene 1
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Monday
04.12.
15:00 - 18:30
Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1 - Tuesday 05.12. 16:45 - 19:15 Seminarraum 1.2, Biologie Djerassiplatz 1, 1.004, Ebene 1
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Monday
11.12.
15:00 - 18:30
Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1 - Tuesday 12.12. 16:45 - 19:15 Seminarraum 1.2, Biologie Djerassiplatz 1, 1.004, Ebene 1
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Monday
08.01.
15:00 - 18:30
Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1 - Tuesday 09.01. 16:45 - 19:15 Seminarraum 1.2, Biologie Djerassiplatz 1, 1.004, Ebene 1
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Monday
15.01.
15:00 - 18:30
Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1 - Tuesday 16.01. 16:45 - 19:15 Seminarraum 1.2, Biologie Djerassiplatz 1, 1.004, Ebene 1
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Monday
22.01.
15:00 - 18:30
Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1 - Tuesday 23.01. 16:45 - 19:15 Seminarraum 1.2, Biologie Djerassiplatz 1, 1.004, Ebene 1
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Monday
29.01.
15:00 - 18:30
Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1 - Tuesday 30.01. 16:45 - 19:15 Seminarraum 1.2, Biologie Djerassiplatz 1, 1.004, Ebene 1
Information
Aims, contents and method of the course
Commonly used statistical techniques with regard to the bachelor thesis and other scientific work shall be understood theoretically and practically, as well as being applied autonomously at the end of the course.There will be one special topic for each lecture.Among others, the following topics will be included.-- Use and abuse of statistics-- Handling of the data: designing a data file, quality assurance-- Descriptive statistics-- When to use which significance test?-- Prerequisites, application, and interpretation of commonly used significance tests-- Tables and figures (what, how, when, where)-- Verbal description of the computed results-- Acquiring statistics autonomously (with instructions)
Assessment and permitted materials
Attendance, oral presentation, active participation and homework (open book), final papers (theoretical part: open book, practice: no books/materials allowed). If switched to a digital mode due to COVID-19, also the practical part is changed to an open book exam.
To safeguard good academic practice, the lecturer may ask students to reflect on their written assignements in a conversation. Students must successfully pass this reflection.
If good scientific practice is violated in any assessment, you will fail to pass the course.
To safeguard good academic practice, the lecturer may ask students to reflect on their written assignements in a conversation. Students must successfully pass this reflection.
If good scientific practice is violated in any assessment, you will fail to pass the course.
Minimum requirements and assessment criteria
The following criteria have to be met in order to pass this course:
Regular attendance (at least 80% in both parts of the course), handing in both final papers, at least 51 credit points. In total, 100 points can be obtained:
Theory (50 points):
Written preparation on a statistical topic (10 points)
Active participation and homework (20 points)
Final paper (20 points)
Practice -- SPSS (50 points):
Homework (20 points)
Final paper (30 points)
Grade 1: 87 – 100 points, Grade 2: 75 – 86,99 points, Grade 3: 63 – 74,99 points, Grade 4: 51 – 62,99 points, Grade 5: < 51 points.
Regular attendance (at least 80% in both parts of the course), handing in both final papers, at least 51 credit points. In total, 100 points can be obtained:
Theory (50 points):
Written preparation on a statistical topic (10 points)
Active participation and homework (20 points)
Final paper (20 points)
Practice -- SPSS (50 points):
Homework (20 points)
Final paper (30 points)
Grade 1: 87 – 100 points, Grade 2: 75 – 86,99 points, Grade 3: 63 – 74,99 points, Grade 4: 51 – 62,99 points, Grade 5: < 51 points.
Examination topics
Each topic is introduced by the lecturers. Demonstrations on the blackboard and in the specific software will support the talk. Examples will be discussed with the students and where possible also practiced in hands-on training during the practicum. Additional literature will be provided via handouts and the elearning-platform. To study each topic in more detail, there will be small written homework to be completed within the following week. Results and questions will then be discussed in class.
Reading list
Materials will be provided via the elearning platform Moodle.
Association in the course directory
BAN 5
Last modified: Th 07.09.2023 15:48