statistik_master:environ_geo:assessment_scheme_laaha

Assessment scheme for advanced lectures with integrated exercises (English)

Information on this page applies to lectures "Environmental statistics" and "Statistics of extreme events and geostatistics" (Prof.Laaha).


Practical part

The evaluation of the practical skills is performed on the basis of smaller exercises and 2-3 homework assignments that are conducted via BOKUlearn.

Smaller exercises: are assigned in the first units of the course. They are counted as "active contribution" and will assist in assigning a grade, e.g. in inconclusive cases (when standing between two grades).

Homework: These larger, obligatory exercises shall be solved using the software R. Some exercises shall be handed in in the form of a small report (pdf file), showing each step of the analysis (R codes, numeric and graphical output, together with stating the main assumptions and giving a short interpretation of the results). Other exercises are proposed as online-exercises where results are directly entered in a web-mask (see declaration of each exercise).

Lecture part

For "Environmental statistics" the evaluation of the knowledge of the course content will be by either a seminary work + final presentation, or by a written exam at the end of the course. A repetition date at the end of the semester will be proposed for those who missed the exam or received a negative grade.

For "Statistics of extreme events and geostatistics" the knowledge of of the course content will be evaluated by a seminary work + final presentation.

Grading

For each part (practical part and lecture part) at least 50% of the maximum possible points are required. Otherwise a negative grade will be given.

The total performance $P$ (% of possible points) is the combined performance of the home exercises $P_H$ and the final exam $P_E$

$$ P = \frac{1}{2}\cdot P_H+ \frac{1}{2}\cdot P_E $$

The following grading scheme is applied:

Total performance Grade
50% ≤ $P$ < 60% genügend (4)
60% ≤ $P$ < 75% befriedigend (3)
75% ≤ $P$ < 90% gut (2)
90% ≤ $P$ ≤ 100% sehr gut (1)
statistik_master/environ_geo/assessment_scheme_laaha.txt · Zuletzt geändert: 2024-10-08 10:52 von Gregor Laaha