Seminar in Statistics (StatSem)

Course content

The purpose of the course is to introduce the student to the reading and presentation of research papers within statistics. It prepares the student for their master's thesis in statistics and it provides the student with a background for choosing a suitable topic and supervisor for their thesis. 

 

The course consists of several seminar tracks within the following overall research areas:

  • Applied statistics
  • Theoretical statistics
  • Statistical methodology
  • Computations and algorithms
  • Probability theory

 

The tracks will be organized so that they present a selection of research papers within one or more of the above research areas to the students. The papers can be a mix of classical papers and recent papers.
 

 

Education

MSc Programme in Statistics
MSc Programme in Mathematics-Economics
MSc Programme in Actuarial Mathematics

Learning outcome

Knowledge:

  • Selected contemporary and classical topics in statistics and probability theory
  • Scientific journals and conferences within statistics and machine learning

 

Skills:

  • Read research level literature within statistics and/or probability theory
  • Present research level problems and solutions orally and in writing
  • Discuss and criticise research papers

 

Competences:

  • Prioritize effort in the process of understanding technical literature
  • Condense and summarize the main points of a technical research paper

Each of the seminar tracks has one seminar each week consisting of 2x45 minutes of oral presentation plus 45 minutes of discussion. The presentations and discussions are given by the course participants.

The tracks do not overlap, and the students can choose to follow one or more seminars each week. The participants are required to attend a minimum of seven seminars during the course.

The course is targeted toward 2nd year MSc students in statistics, and participants are expected to have corresponding mathematical and statistical qualifications, e.g by having passed the MSc courses Regression, Stat A and Stat B.

Oral
Collective
Continuous feedback during the course of the semester
Peer feedback (Students give each other feedback)
ECTS
7,5 ECTS
Type of assessment
Continuous assessment
Type of assessment details
The exam is composed of five elements that are to be completed during the course. Four of the elements are based on the scientific papers and consist of: one oral paper presentation; one oral paper discussion; two written paper synopses. As the fifth element, the students must attend a minimum of seven seminars during the course.
Each of the five elements of the exam must be passed separately to pass the course.
Marking scale
passed/not passed
Censorship form
No external censorship
One internal examiner
Re-exam

Passed exam elements can be reused for the reexam the same year.

If the student has not attended a minimum of seven seminars, one additional written paper synopsis must be handed in, whence the reexam requires a total of three written paper synopses.

 

If a synopsis is not passed during the ordinary exam, a new synopsis must be handed in for the reexam.

 

If one or both of the oral elements are not passed during the ordinary exam, the reexam will include a 25 minutes oral exam without preparation time consisting of a 15 minutes paper presentation and a 10 minutes discussion.  

Criteria for exam assessment

The student should convincingly and accurately demonstrate the knowledge, skills and competences described under Intended learning outcome.

Single subject courses (day)

  • Category
  • Hours
  • Preparation
  • 100
  • Seminar
  • 21
  • Exam Preparation
  • 60
  • Exam
  • 25
  • English
  • 206

Kursusinformation

Language
English
Course number
NMAK22014U
ECTS
7,5 ECTS
Programme level
Full Degree Master
Duration

1 block

Placement
Block 1
Schedulegroup
B
Capacity
The number of seats may be reduced in the late registration period
Studyboard
Study Board of Mathematics and Computer Science
Contracting department
  • Department of Mathematical Sciences
Contracting faculty
  • Faculty of Science
Course Coordinators
  • Niels Richard Hansen   (14-7b767279803b7f3b756e7b80727b4d7a6e81753b78823b7178)
  • Bo Markussen   (5-6673716576447165786c326f7932686f)
  • Jun Yang   (2-79884f7c7083773d7a843d737a)
Saved on the 25-08-2023

Are you BA- or KA-student?

Are you bachelor- or kandidat-student, then find the course in the course catalog for students:

Courseinformation of students