Entry requirements

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

Learning outcomes

On completion of the course, the student should be able to:

• apply basic and advanced knowledge in statistical analysis
• plan collection of data in a way that they can be analysed with chosen statistical methods
• choose relevant methods for statistical analysis of environmental data
• 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 (2 credits) and presentation of statistical problem-solving (5 credits). Oral and written presentation of statistical data (3 credits).

If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the disability coordinator of the university.