Universität Wien

300322 VU Biological Data: introduction to statistics and SPSS (2024W)

9.00 ECTS (6.00 SWS), SPL 30 - Biologie
Continuous assessment of course work
Moodle
Mo 16.12. 15:00-18:15 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1

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. 24 participants
Language: German

Lecturers

Classes (iCal) - next class is marked with N

Attendance compulsory at the kick-off meeting: Those who do not attend without prior notice (sonja.windhager@univie.ac.at) will be deregistered so that students from the waiting list succeed.

  • Tuesday 01.10. 16:45 - 19:15 Seminarraum 1.5, Biologie Djerassiplatz 1, 1.012, Ebene 1
  • Monday 07.10. 15:00 - 18:15 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
    Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
  • Tuesday 08.10. 16:45 - 19:15 Seminarraum 1.5, Biologie Djerassiplatz 1, 1.012, Ebene 1
  • Monday 14.10. 15:00 - 18:15 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
    Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
  • Tuesday 15.10. 16:45 - 19:15 Seminarraum 1.5, Biologie Djerassiplatz 1, 1.012, Ebene 1
  • Monday 21.10. 15:00 - 18:15 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
    Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
  • Tuesday 22.10. 16:45 - 19:15 Seminarraum 1.5, Biologie Djerassiplatz 1, 1.012, Ebene 1
  • Monday 28.10. 15:00 - 18:15 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
    Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
  • Tuesday 29.10. 16:45 - 19:15 Seminarraum 1.5, Biologie Djerassiplatz 1, 1.012, Ebene 1
  • Monday 04.11. 15:00 - 18:15 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
    Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
  • Tuesday 05.11. 16:45 - 19:15 Seminarraum 1.5, Biologie Djerassiplatz 1, 1.012, Ebene 1
  • Monday 11.11. 15:00 - 18:15 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
    Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
  • Tuesday 12.11. 16:45 - 19:15 Seminarraum 1.5, Biologie Djerassiplatz 1, 1.012, Ebene 1
  • Monday 18.11. 15:00 - 18:15 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
    Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
  • Tuesday 19.11. 16:45 - 19:15 Seminarraum 1.5, Biologie Djerassiplatz 1, 1.012, Ebene 1
  • Monday 25.11. 15:00 - 18:15 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
    Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
  • Tuesday 26.11. 16:45 - 19:15 Seminarraum 1.5, Biologie Djerassiplatz 1, 1.012, Ebene 1
  • Monday 02.12. 15:00 - 18:15 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
    Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
  • Tuesday 03.12. 16:45 - 19:15 Seminarraum 1.5, Biologie Djerassiplatz 1, 1.012, Ebene 1
  • Monday 09.12. 15:00 - 18:15 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
    Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
  • Tuesday 10.12. 16:45 - 19:15 Seminarraum 1.5, Biologie Djerassiplatz 1, 1.012, Ebene 1
  • Tuesday 17.12. 16:45 - 19:15 Seminarraum 1.5, Biologie Djerassiplatz 1, 1.012, Ebene 1
  • Tuesday 07.01. 16:45 - 19:15 Seminarraum 1.5, Biologie Djerassiplatz 1, 1.012, Ebene 1
  • Monday 13.01. 15:00 - 18:15 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
    Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
  • Tuesday 14.01. 16:45 - 19:15 Seminarraum 1.5, Biologie Djerassiplatz 1, 1.012, Ebene 1
  • Monday 20.01. 15:00 - 18:15 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
    Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
  • Tuesday 21.01. 16:45 - 19:15 Seminarraum 1.5, Biologie Djerassiplatz 1, 1.012, Ebene 1
  • Monday 27.01. 15:00 - 18:15 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
    Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
  • Tuesday 28.01. 16:45 - 19:15 Seminarraum 1.5, Biologie Djerassiplatz 1, 1.012, 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).

To safeguard good academic practice, the lecturer may ask students to reflect on their written assignments 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.

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: We 21.08.2024 19:46