Entry requirements

60 credits in science or social sciences, including 5 credits in statistics

Learning outcomes

After passing the course the student shall be able to:

• apply basic and advanced knowledge in statistical analysis
• choose relevant methods for statistical treatment of various types of datasets
• plan collection of data in a way that they can be analysed with chosen statistical methods
• analyse data that are correlated with several parameters synchronously
• analyse long term datasets
• collect and evaluate current environmental data
• present data in tables and diagrams

Content

The course contents include evaluation and analysis of environmental data as well as presentation of data and analysis results. The course is focusing on statistical methods that are specifically designed for treatment of environmental data, for example multivariate analysis methods, such as multipel regression, ordination and factorial analysis, that are used for analysis of data that are correlated with several environmental parameters simultaneously. The course also includes methods for trend analysis of long term environmental datasets. The course contents can be seen as a supplement to earlier basic knowledge in statistics.

Instruction

Lectures and supervised practical exercises.

Assessment

Written examination in statistical theory (3 credits) and statistical problem-solving (5 credits). Oral and written presentation of statistical data (2 credits).