Objectives:
The overall goal of the course is to be a direct contributor to calculations and analyses to be included in the student's MSc or PhD thesis. A secondary goal is that the student learns to do basic calculations and analyses with the software programming language Python.
Content:
The teaching is focused on exercises using Python software. Through applications the students are presented to basic concepts and problems of data analysis in general (variables, significance, confidence, hypothesis testing, p-value, statistical test methods, model choice, experimental design, etc.) The course includes time series analysis as well as analysis on spatial data. The weighting of these topics will depend on the students¿ background . At the end of the course the students deliver a term paper. Here, it is recommended that the students are using data from their own MSc or PhD work.
On completion of the course the student should have the following learning outcomes defined in terms of knowledge, skills and general competence:
Knowledge
The student
Skills
The student
General competence
The student
Mandatory participation in collective working sessions (at least 75% of the allotted time)
Mandatory participation at seminar
The following forms of assessment are used in the course:
Portfolio Assessment
The student coordinator can be contacted here:
Studierettleiar@geo.uib.no