751-3801-00L  Experimental Design and Applied Statistics in Agroecosystem Science

SemesterAutumn Semester 2017
LecturersA. Hund, W. Eugster, C. Grieder, R. Kölliker
Periodicityyearly recurring course
Language of instructionGerman



Courses

NumberTitleHoursLecturers
751-3801-00 GExperimental Design and Applied Statistics in Agroecosystem Science
Course will be held in German unless there are students present who ask for English lecturing. Handouts are in English. Students should be aware that in addition to 2 weeks of presence during the course there are 3-5 hours per week of individual study necessary to fulfill the targets of this course.
2 hrs
Thu10:15-12:00HG E 19 »
A. Hund, W. Eugster, C. Grieder, R. Kölliker

Catalogue data

AbstractIn this course, different experimental designs will be discussed and various statistical tools will be applied to research questions in agroecosystem sciences. Both manipulative (field and laboratory) experiments and surveys are addressed and students work with a selection of basic techniques and methods to analyse data using a hands-on approach. Methods range from simple t-tests to multi-factoria
ObjectiveStudents will know various statistical analyses and their application to science problems in their study area as well as a wide range of experimental design options used in environmental and agricultural sciences. They will practice to use statistical software packages (R), understand pros and cons of various designs and statistics, and be able to statistically evaluate their own results as well as those of published studies.
ContentThe course program uses a learning-by-doing approach ("hands-on minds-on"). New topics are introduced in the lecture hall, but most of the work is done in the computer lab to allow for the different speeds of progress of the student while working with data and analyzing results. In addition to contact hours exercises must be finalized and handed in for grading. The credit points will be given based on successful assessments of selected exercises.

The tentative schedule containst the following topics:

Introduction To Experimental Design and Applied Statistics
Introduction to 'R' / Revival of 'R' Skills
Designs of Field and Growth Chamber Experiments
Nonlinear Regression Fits
Multivariate Techniques: Principle Component Analysis, Canonical Correpondence Analysis (CCA), Cluster Analysis
ANOVA using linear and mixed effect models
Error Analysis, Error Propagation and Error Estimation
Introduction to autoregression and autocorrelations in temporal and spatial data and how to consider them in ANOVA-type analysis

This course does not provide the mathematical background that students are expected to bring along when signing up to this course. Alternatively, students can consider some aspects of this course as a first exposure to solutions in experimental design and applied statistics and then deepen their understanding in follow-up statistical courses.
Lecture notesHandouts will be available (in English)
LiteratureA selection of suggested additional literature, especially for German speaking students will be presented in the introductory lecture.
Prerequisites / NoticeThis course is based on the course Mathematik IV: Statistik, passed in the 2nd year and the Bachelor's course "Wissenschaftliche Datenauswertung und Datenpräsentation" (751-0441-00L)

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits3 credits
ExaminersA. Hund, W. Eugster, C. Grieder, R. Kölliker
Typegraded semester performance
Language of examinationEnglish
RepetitionRepetition possible without re-enrolling for the course unit.
Admission requirementWritten Exercises (for course attendants only) on select topics of the course throughout the semester (ca. 7 exercises)
Additional information on mode of examinationStudents can use either German, English, or French in their written work; docents will typically reply in German or English.

Learning materials

No public learning materials available.
Only public learning materials are listed.

Groups

No information on groups available.

Restrictions

There are no additional restrictions for the registration.

Offered in

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