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n.BA.AD.AES.23HS (Applied Environmental Statistics) 
Module: Applied Environmental Statistics
This information was generated on: 03 July 2025
No.
n.BA.AD.AES.23HS
Title
Applied Environmental Statistics
Credits
2

Description

Version: 3.0 start 01 August 2024

 

Study Programme Applied Digital Life Sciences
Regulations Applicable RPO, 29 January 2008, School of Life Sciences and Facility Management Academic Regulations, 15 Dec. 2009, Annex for the Bachelor of Applied Digital Life Sciences degree programme
Module Type  
X Compulsory Module    Elective Module    Optional Module
Planned Semester 4th Semester
Module Coordinator Stefan Widmer
Telephone / E-Mail +41 (0)58 934 58 62 / stefan.widmer@zhaw.ch
Lecturer(s),
Speaker(s),
Associate(s)		 Stefan Widmer, Jürgen Dengler
Entrance Requirements Statistik und Wahrscheinlichkeit, Statistische Modellierung und Simulation, Versuchsplanung und Auswertung
Learning Outcomes and Competencies Theoretical skills:
The students
  • understand how to sample and organise their data to apply statistical methods on these
  • are able to implement a wide range of statistical methods in the programming language R to real-world datasets to answer questions in ecology and environmental sciences
  • are able to present and interpret statistical outputs appropriately.
Transferable skills:
The students
  • use a wide range of sources to find solutions to statistical problems
Module Content
  • Experimental and sampling designs in ecology
  • Repetition of simple statistical methods and their prerequisites
  • Linear and Polynomial Regression
  • Information theoretician approach and multi-model inference
  • Generalized linear models (GLMs)
  • Linear mixed-effect models (LMMs)
  • Ordinations
  • Cluster analyses
Follow-up Modules Advanced Environmental Statistics, Computational modelling in environmental sciences
Methods of Instruction  Lectures: Short inputs to review or introduce the theoretical basis of the discussed methods.

Demonstration: Practical introduction of methods new to the students in R

Exercises: Exercises presented in the lecture, which can then be started in supervised self-study and completed as homework. The homework will usually be discussed in the next class.
Digital Resources
  • Moodle
  • Practical exercises in R with commented example solutions
  • Scientific papers on specific topics
Lesson Structure / Workload  
 Contact Hours 28
 Guided Self-Study 14
 Independent Self-Study 18
 Total Workload 60
Classroom Attendance Attendance is encouraged, but not enforced with attendance list
Assessment
  • Written exam at the end of the semester (60%)
  • Coursework (40%)
If there is a low number of participants, the lecturer may change the form of a repeat examination after consultation with the head of the study programme: e.g. an oral examination can be used to replace a written one. Please report any changes to the form of examinations by e-mail to pruefungsadmin.lsfm@zhaw.ch and Cc. Head of study programme
Language of Instruction  English
Comments -

 

Note

Course: Applied Environmental Statistics
No.
n.BA.AD.AES.23HS.V
Title
Applied Environmental Statistics

Note

  • No module description is available in the system for the cut-off date of 03 July 2025.