Data Analysis and Modelling for Aquatic Ecosystems

The course contains different (statistical) data analysis techniques for handling ecological data sets using MS Excel and R software and dynamic simulation modelling with Stella

Apply now for

2020

For whom?

Students in the Limnology and Wetland Management specialisation of the IHE Environmental Science MSc-programme; students from other academic institutions who take this module as a short course; professionals working in the water or environment sector who want to strengthen their skills in quantitative data analysis.

Prerequisites

For LWM students: prerequisites of the LWM specialization; for course participants from outside IHE: a basic knowledge of statistics (e.g. from having taken a university course in basic statistics or from work experience), and basic skills in working with Excel spreadsheets.

Dates, Fee, ECTS

Start: 18 May 2020
End: 05 June 2020
ECTS credit points: 5
Deadline IHE application: 17 April 2020 - 23.59 (CET)
Course fee: € 2910

VAT is not included in the course fee

Learning objectives

Upon completion, the participant should be able to:
  1. Store and manipulate experimental data efficiently in a simple database and perform exploratory data analysis using time series plots, scatter plots and descriptive statistics in MS Excel and R.
  2. Perform basic statistical procedures and analyses using R (distribution tests and transfor-mations, t-tests, ANOVAs, non-parametric tests, simple and multiple regression, etc.)
  3. Do multivariate statistical analyses, such as multiple regression analysis and factor analysis, using R; and understand the principles of some other advanced modelling applications for ecological data.
  4. Construct a simple dynamic simulation model of an aquatic ecosystem using Stella.
  5. Discuss critically the strengths, weaknesses, missing information, advantages and disadvantages of the analyses.
  6. Communicate effectively the methods, results and conclusions of a case study (presentation and written report).

Share

Connect with us

Never miss a thing!