Revised by: Rector of Umeå School of Business and Economics, 2021-06-24
Contents
During the course the student will individually perform a statistical work presented in a scientific paper. The work may consist of statistical data analysis, evaluation of statistical methods or review and summary of literature on some statistical area. The subject dealt with may be linked to ongoing research at the university, be a deepening of the work of a consulting nature or treat one's own area of interest. The thesis can be an extension of the Bachelor thesis or totally independent. The thesis is presented and defended orally at an open seminar. The course also includes examination, evaluation and discussion of other students' theses.
Expected learning outcomes
Having completed the course the student should be able to:
demonstrate advanced knowledge in an area of statistical science;
independently seek and evaluate statistical knowledge;
independently formulate, define and analyze a statistical problem;
report in writing, with scientific documentation technique, an independent scientific statistical work;
orally present and defend an independent scientific statistical work;
examine, evaluate and discuss fellow students theses;
provide statistical knowledge to people without specialist knowledge in statistics;
demonstrate the ability to accomplish independent work within specified time limits.
Required Knowledge
Univ: 15 ECTS advanced level in statistics or equivalent. Proficiency in English equivalent to Swedish upper secondary course English B/6
Form of instruction
The course consists of tutorials and seminars, where some of the seminars are mandatory. Supervision is provided only for the time when the course is in progress.
Examination modes
The thesis must be presented and defended at a mandatory seminar. The student must also oppose on another thesis in statistics. To pass the course requires, in addition to an approval of the thesis, also that the presentation and the defense of the thesis, as well as the opposition on another thesis are approved. Also, to pass the course the student must actively participate during the other mandatory seminars during the course.
The grades awarded on the course are: G (Pass), U (Fail), VG (Pass with distinction). Grades on the course are awarded when students have passed all examinations in the course. The grade is a comprehensive evaluation of the results of the various parts of the examinations and is not granted until all mandatory tasks have been passed.
A student who has passed an examination is not allowed to take another examination in order to get a higher grade. For students who do not pass, an additional test will be held according to a pre-determined schedule. After two failed examinations on the course, the student has the right to request another grading teacher. Written requests should be handed to the Director of Studies no later than two weeks before the date of the next examination.
Exceptions from examination form as stated in the syllabus can be made for a student who has a decision on pedagogical support for disabilities. Individual adaptations of the examination form should be considered based on the student's needs. The examination form shall be adapted within the framework of the expected learning outcomes stated in the course syllabus. At the request of the student, the course responsible teacher, in consultation with the examiner, must promptly decide on the adapted examination form. The decision must then be notified to the student.
Students may request an examination in accordance with this syllabus up to three times over a two year period following its expiry.
Academic credit transfer Academic credit transfers are according to the University credit transfer regulations.
Other regulations
Note that the course is an on-campus course, which means that the student is expected to attend the seminars and meet with the supervisor at Umeå university campus. It is not possible to take the course online.
A Guide for Ethical Data Science A collaboration between the Royal Statistical Society (RSS) and the Institute and Faculty of Acturaries (IFoA) Royal Statistical Society (RSS) and the Institute and Faculty of Acturaies (IFoA) : 2019 : https://www.actuaries.org.uk/documents/guide-ethical-data-science Mandatory
Complementary literature relevant for the thesis project.
Mandatory.