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| Title |
Data Analysis and Modelling in Environmental Science
|
| Semester |
E2024
|
| Master programme in |
Environmental Science
|
| Type of activity |
Course |
| Teaching language |
English
|
| Study regulation | |
| REGISTRATION AND STUDY ADMINISTRATIVE | |
| Registration |
Sign up for study activities at STADS Online Student Service within the announced registration period, as you can see on the Study administration homepage. When signing up for study activities, please be aware of potential conflicts between study activities or exam dates. The planning of activities at Roskilde University is based on the recommended study programs which do not overlap. However, if you choose optional courses and/or study plans that goes beyond the recommended study programs, an overlap of lectures or exam dates may occur depending on which courses you choose. |
| Number of participants |
|
| ECTS |
5
|
| Responsible for the activity |
Morten Foldager Pedersen (mfp@ruc.dk)
|
| Head of study |
Per Meyer Jepsen (pmjepsen@ruc.dk)
|
| Teachers |
|
| Study administration |
INM Registration & Exams (inm-exams@ruc.dk)
|
| Exam code(s) |
U60093
|
| ACADEMIC CONTENT | |
| Overall objective |
This is a theoretical and practical course (including lectures, class-room exercises and a mini-project) that will train students in the design of environmental surveys and impact studies, and to statistically analyse and evaluate data from such investigations. Focus will be on statistical techniques needed to evaluate temporal changes in environmental variables (i.e., time-series analyses) and on impact assessment. The course introduces further students to the design, construction and use of simple dynamic models (i.e., ‘predictive models’) used for environmental analysis and evaluation. |
| Detailed description of content |
This is a theoretical and practical course (including lectures, class-room exercises and a mini-project). The first two thirds of the course focus on statistical methods commonly used in Environmental science, while the last third of the course focus on the application of dynamic modeling in environmental assessments. The course relies to a large extent on "hands-on" practice and the intention is to train students in the design of environmental surveys and impact studies, and to statistically analyse and evaluate data from such investigations. Focus will be on statistical techniques needed to conduct impact assessments (e.g. ANOVA) and methods used to analyze temporal changes in environmental variables such as changes in population size or changes in physical-chemical variables (i.e. time-series analyses). The course introduces further students to the design, construction and use of simple dynamic models (i.e. ‘predictive models’) used for environmental analysis and evaluation. |
| Course material and Reading list |
There is no formal text-books in this course. The curriculum consists of:
All material will be freely available from the course Moodle folder. |
| Overall plan and expected work effort |
The course consists of ca. 20 lectures/exercises, each 2 hours (=2*45 minutes). The course is a 5 ETCS credit course, corresponding to an expected student work-load of ca. 135 hours divided between;
About 75% of the lectures will be practical exercises where students will analyze data (or design and construct a dynamic model) in small groups and under supervision from the teacher. Students must expect to meet and finish some of the exercises outside ordinary class hours as part of their preparation (i.e. without supervision from the teacher). |
| Format |
|
| Evaluation and feedback |
The course includes formative evaluation based on dialogue between the students and the teacher(s). Students are expected to provide constructive critique, feedback and viewpoints during the course if it is needed for the course to have better quality. Every other year at the end of the course, there will also be an evaluation through a questionnaire in SurveyXact. The Study Board will handle all evaluations along with any comments from the course responsible teacher. Furthermore, students can, in accordance with RUCs ‘feel free to state your views’ strategy through their representatives at the study board, send evaluations, comments or insights form the course to the study board during or after the course. |
| Programme |
The program consists of ca. 20 lectures (each 2 hours) over a 8 week period. Note that the exact program may change slightly from year to year depending on needs. The major topics are:
|
| ASSESSMENT | |
| Overall learning outcomes |
Having completed the course, students will be able to:
|
| Form of examination |
Portfolio written in a group or individually
Permitted group size: 2-4 students. Examples of written products are exercise responses, talking points for presentations, written feedback, reflections, written assignments. The preparation of the products may be subject to time limits. The content of the portfolio must be individualised. The character limits of the portfolio are : For 1 student: 12,000-72,000 characters, including spaces. For 2 students: 12,000-72,000 characters, including spaces. For 3 students: 12,000-72,000 characters, including spaces. For 4 students: 12,000-72,000 characters, including spaces. The character limits include the cover, table of contents, bibliography, figures and other illustrations, but exclude any appendices. The portfolio's specific products and the (if relevant) recommended size (character limits) for the individual products are made public on study.ruc.dk before the course begins. The entire portfolio must be handed in at the same time (uploaded to eksamen.ruc.dk). Handing in the portfolio or parts of the portfolio to the supervisor for feedback, cannot replace the upload to eksamen.ruc.dk. The submission deadline will be announced on study.ruc.dk before the course begins. Assessment: Pass/Fail |
| Form of Re-examination |
Samme som ordinær eksamen / same form as ordinary exam
|
| Type of examination in special cases |
|
| Examination and assessment criteria |
Students will be assessed by their ability to:
|
| Exam code(s) | |
| Last changed | 16/02/2024 |
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