Universität Wien
Warning! The directory is not yet complete and will be amended until the beginning of the term.

300044 VU Statistical analysis in practice: from raw data to presentation (2024W)

3.00 ECTS (2.00 SWS), SPL 30 - Biologie
Continuous assessment of course work
Moodle
Fr 24.01. 13:15-14:45 Seminarraum 1.7, Biologie Djerassiplatz 1, 1.010, 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. 40 participants
Language: German

Lecturers

Classes (iCal) - next class is marked with N

THE COURSE ON OCT. 4 WILL ONLY TAKE PLACE VIA ZOOM (access via Moodle or email to sonja.windhager@univie.ac.at)
The exact dates are still to be announced. There are six dates for the course and an additional one for the final tasks (two options, one must be chosen). After the registration period ended, you will receive an email to indicate your preferences. The dates will be fixed in the kick-off meeting.
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.

  • Friday 04.10. 13:15 - 14:45 Seminarraum 1.7, Biologie Djerassiplatz 1, 1.010, Ebene 1
  • Friday 04.10. 15:00 - 16:30 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
    Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
  • Friday 11.10. 13:15 - 14:45 Seminarraum 1.7, Biologie Djerassiplatz 1, 1.010, Ebene 1
  • Friday 11.10. 15:00 - 16:30 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
    Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
  • Friday 18.10. 13:15 - 14:45 Seminarraum 1.7, Biologie Djerassiplatz 1, 1.010, Ebene 1
  • Friday 18.10. 15:00 - 16:30 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
    Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
  • Friday 25.10. 13:15 - 14:45 Seminarraum 1.7, Biologie Djerassiplatz 1, 1.010, Ebene 1
  • Friday 25.10. 15:00 - 16:30 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
    Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
  • Friday 08.11. 13:15 - 14:45 Seminarraum 1.7, Biologie Djerassiplatz 1, 1.010, Ebene 1
  • Friday 08.11. 15:00 - 16:30 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
    Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
  • Friday 15.11. 13:15 - 14:45 Seminarraum 1.7, Biologie Djerassiplatz 1, 1.010, Ebene 1
  • Friday 15.11. 15:00 - 16:30 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
    Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
  • Friday 22.11. 13:15 - 14:45 Seminarraum 1.7, Biologie Djerassiplatz 1, 1.010, Ebene 1
  • Friday 22.11. 15:00 - 16:30 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
    Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
  • Friday 29.11. 13:15 - 14:45 Seminarraum 1.7, Biologie Djerassiplatz 1, 1.010, Ebene 1
  • Friday 29.11. 15:00 - 16:30 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
    Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
  • Wednesday 04.12. 15:00 - 16:30 Seminarraum 1.4, Biologie Djerassiplatz 1, 1.013, Ebene 1
  • Friday 06.12. 13:15 - 14:45 Seminarraum 1.7, Biologie Djerassiplatz 1, 1.010, Ebene 1
  • Friday 06.12. 15:00 - 16:30 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
    Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
  • Friday 13.12. 13:15 - 14:45 Seminarraum 1.7, Biologie Djerassiplatz 1, 1.010, Ebene 1
  • Friday 13.12. 15:00 - 16:30 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
    Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
  • Wednesday 08.01. 15:00 - 16:30 Seminarraum 1.4, Biologie Djerassiplatz 1, 1.013, Ebene 1
  • Friday 10.01. 13:15 - 14:45 Seminarraum 1.7, Biologie Djerassiplatz 1, 1.010, Ebene 1
  • Friday 10.01. 15:00 - 16:30 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
    Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
  • Friday 17.01. 13:15 - 14:45 Seminarraum 1.7, Biologie Djerassiplatz 1, 1.010, Ebene 1
  • Friday 17.01. 15:00 - 16:30 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
    Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
  • Friday 24.01. 15:00 - 16:30 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
    Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
  • Friday 31.01. 13:15 - 14:45 Seminarraum 1.7, Biologie Djerassiplatz 1, 1.010, Ebene 1
  • Friday 31.01. 15:00 - 16:30 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
    Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1

Information

Aims, contents and method of the course

This course deals with the organization, analysis, interpretation and presentation of data. It gives an overview of basic statistic techniques, which will be practised in course. The focus in terms of software is on SPSS, however, other programs will be mentioned. The course shall lead to a better understanding which methods and visual displays should be used when (and why). The analyses can be applied and interpreted correctly.

Assessment and permitted materials

Requirements for the course: regular attendance + oral (discussions, answering questions in class) + short written homework + longer homeworks+practical final test. Material allowed: Homework (all, open book), final test (none; open book only of digital mode becomes necessary).
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

It is necessary to have at least 51 points (out of 100) to pass the course: participation and practice 10 points, longer home work (40 points, two-times 20), practical final test 50 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.
Attendance compulsory (at least 80% required to pass the course).

Examination topics

Short lectures will give an overview. There will software demonstrations. Examples will be discussed with the students and practiced in hands-on training. There will be small written homework to be completed within the following week. Results and questions will then be discussed in class. Moreover, there will be two extended tasks und a final test.

Reading list

Further material will be provided via handouts and the learning platform Moodle.

Association in the course directory

BAN 5

Last modified: Fr 22.11.2024 18:46