Special Aspects of Statistics and Experimental Design
- Faculty
Faculty of Agricultural Science and Landscape Architecture
- Version
Version 2 of 03.05.2023.
- Module identifier
44B0678
- Module level
Bachelor
- Language of instruction
German
- ECTS credit points and grading
5.0
- Module frequency
only winterterm
- Duration
1 semester
- Brief description
In many areas of horticulture, in-depth knowledge of specific statistical methods is required. Obtaining characteristic data to control production requires special knowledge of the planning and evaluation of experiments and of data acquisition, in order to then arrive at correct decisions through proper statistical evaluation, naturally taking into account a certain risk of error.
- Overall workload
The total workload for the module is 135 hours (see also "ECTS credit points and grading").
- Teaching and learning methods
Lecturer based learning Hours of workload Type of teaching Media implementation Concretization 32 Lecture Online - 20 Practice Online - 5 Other Online - Lecturer independent learning Hours of workload Type of teaching Media implementation Concretization 28 Preparation/follow-up for course work - 10 Study of literature - 25 Exam preparation - 15 Work in small groups -
- Graded examination
- Portfolio exam or
- Written examination or
- oral exam
- Remark on the assessment methods
The standard type of examination is portfolio examination (in case of deviation, one of the alternative examination types mentioned will be selected by the examiner and announced at the beginning of the course)
- Exam duration and scope
The portfolio exam consists of the sub-exams:
E-exam (30 min., max. 25%) + E-exam (30 min., max. 25%) + written exam (60 min., max. 50% of the total number of points to be achieved)
- Literature
Dormann, Carsten F. Parametrische Statistik. Springer Berlin Heidelberg, 2013.
Wickham, Hadley, and Garrett Grolemund. R for data science: import, tidy, transform, visualize, and model data. O'Reilly Media, Inc., 2016. [https://r4ds.had.co.nz/]
Köhler, Wolfgang, Gabriel Schachtel, and Peter Voleske. Biostatistik: Einführung in die Biometrie für Biologen und Agrarwissenschaftler. Springer-Verlag, 2013.
Data Science for Agriculture in R unter schmidt-paul.github.io/DSFAIR/
- Applicability in study programs
- Pflanzentechnologie in der Agrarwirtschaft
- Pflanzentechnologie in der Agrarwirtschaft B.Sc.
- Person responsible for the module
- Ulbrich, Andreas
- Further lecturer(s)
Schlehuber, Dennis