Applied Statistics and Experiments
- Faculty
Faculty of Agricultural Science and Landscape Architecture
- Version
Version 2 of 03.05.2023.
- Module identifier
44B0665
- Module level
Bachelor
- Language of instruction
German
- ECTS credit points and grading
5.0
- Module frequency
only summerterm
- Duration
1 semester
- Brief description
Progress in plant and horticulture is essentially supported by intensive experimental activity. In order to be successful in this field, statistical knowledge is required, as well as knowledge of the techniques for carrying out experiments. Measurement data and observations from surveys and trials are evaluated, presented and interpreted using statistical methods. Data-based risk assessment of decisions is practiced.
- 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 or
- Homework / Assignment or
- Oral presentation, with written elaboration
- 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)
- Recommended prior knowledge
Contents of the module 'Introduction to Statistics'.
- 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.
- 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