Universität Wien FIND

270225 SE Statistical Methods with Python (2021W)

3.00 ECTS (2.00 SWS), SPL 27 - Chemie
Continuous assessment of course work


Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).


max. 15 participants
Language: German



Vorbesprechung: 11.10.2021
Veranstaltung: 11.11. - 16.12.2021
Veranstaltung findet in digitaler Form wöchentlich Donnerstags von 10 – 12 Uhr statt


Aims, contents and method of the course

Python is an easy to learn programming language, rich in its application possibilities and offers a multitude of scientific libraries for easy applications of (complex) methods. That is statistical methods, among others. These methods are necessary to corroborate results from scientific experiments (e.g., as in fields of analytical chemistry as lipidomics, proteomics, metabolomics) with statistical evidence. A crucial part is here the illustration of results in form of diagrams and mathematical figures.
You acquire the ability to write own Python scripts with a special focus on the necessities within the analytical chemistry (t-Test,volcano plots, multiple testing, plotting of results, loading and editing tables).
In this course, the first part will be dedicated to the introduction into Python and its most important libraries (matplotlib, numpy, padnas, scipy). In the second part, statistical and further analytical methods (t-test, multiple testing, ANOVA, statistical power, regression) will be explained with examples.
The contents of the courses are worked out by the participants on own responsibility. The participants can choose if to present their topic within a presentation (40 min) with slides or in an interactive session live on the computer (40 min). The sessions are closed by a discussion round (10 min). Die issues within a topic can either be picked by the participants or will be specified by the supervisor. The participants have to provide a term paper with 6 - 10 pages. At the end of the course, all papers will be merged into a single document by the supervisor and distributed to the participants for further application within or after studies.

Assessment and permitted materials

Type of performance control:
• Presentation of a chosen topic during the seminar
• Timely submission of a term paper of 6 – 10 pages

To ensure good scientific practice, the course management can invite students to a grade-relevant discussion after the presentation and submission of the term paper, which must be completed positively.

Minimum requirements and assessment criteria

Minimum requirements:
Attendance at the first unit of the seminar is compulsory. The attendance must be 75% fulfilled.

To achieve a positive grade, 60% of the maximum possible number of points must be achieved. Each part of the performance must be completed at the end of the course.

Assessment standard
100 points can be achieved for this course. These are divided into:
• Presentation and questions: 50 points
• Term paper on the topic: 50 points

The grades are awarded according to the following point scheme:
• 1 (very good): 100 - 91 points
• 2 (good): 90-81 points
• 3 (satisfactory): 80-71 points
• 4 (sufficient): 70-61 points
• 5 (insufficient): 60-0 points

Examination topics

Reading list

Literature & References
In order to achieve the above learning goals, supporting literature and references will be provided.

Association in the course directory

AN-1, AN-2, AN-5, CHE II-1, A.5, Doktorat

Last modified: We 29.09.2021 14:09