Universität Wien

300037 VU Statistical analysis in practice: from raw data to presentation (2020W)

3.00 ECTS (2.00 SWS), SPL 30 - Biologie
Continuous assessment of course work
Moodle

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. 50 participants
Language: German

Lecturers

Classes (iCal) - next class is marked with N

Due to COVID-19, the course will be conducted online (mode: digital) on Fridays 2:00 p.m. until 5 p.m. (more details below).

KICK-OFF MEETING: online (digital)
on Friday, Oct 2, 2 p.m.
Login details will be shared via email after the course registration process is completed. Those who do not attend, will be deregistered so that students from the waiting list succeed, if they have not excused themselves in written form in advance (email to sonja.windhager@univie.ac.at).

There are six dates for the course and an additional one for the final tasks (two options, one needs to be chosen). The course dates are Oct. 9, Oct. 16, Oct. 23., Nov. 6, Nov. 13, Nov. 20, optional for questions: Dec 4. Alternatives for the final tasks: Dec. 11, Dec. 18.

It is recommended to use a personal computer or laptop and to purchase an individual SPSS license (approx. 30 Euro for 1 year via u:soft). This is not obligatory though.

  • Friday 02.10. 14:30 - 15:30 Digital (Kickoff Class)
  • Friday 09.10. 14:00 - 17:00 Digital
  • Friday 16.10. 14:00 - 17:00 Digital
  • Friday 23.10. 14:00 - 17:00 Digital
  • Friday 06.11. 14:00 - 17:00 Digital
  • Friday 13.11. 14:00 - 17:00 Digital
  • Friday 20.11. 14:00 - 17:00 Digital
  • Friday 04.12. 14:00 - 17:00 Digital
  • Friday 11.12. 14:00 - 17:00 Digital
  • Friday 18.12. 14:00 - 17:00 Digital

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 homeworks + longer homeworks+practical final test. Material allowed: Homework (all, open book), final test (open book).
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 12.05.2023 00:23