Statistics, Bayesian Statistics, Second Cycle, 7.5 credits

Aims and objectives

General aims for second cycle education

Second-cycle courses and study programmes shall involve the acquisition of specialist knowledge, competence and skills in relation to first-cycle courses and study programmes, and in addition to the requirements for first-cycle courses and study programmes shall

• further develop the ability of students to integrate and make autonomous use of their knowledge
• develop the students' ability to deal with complex phenomena, issues and situations, and
• develop the students' potential for professional activities that demand considerable autonomy, or for research and development work.

(Higher Education Act, Chapter 1, Section 9)

Course objectives

Knowledge and Understanding

After completed studies, the student shall have

• Understanding of basic concepts in Bayesian Statistics
• Knowledge of the principles underlying the design of a Bayesian Statistical model
• Knowledge of modern simulation based computational methods for Bayesian statistical analysis.

Competence and Skills

After completed studies, the student shall be able to

• Independently formulate a suitable statistical model including the choice of prior distribution
• Communicate relevant aspects of the modeling problem and the results of the statistical analysis.

Judgement and Approach

After completed studies, the student shall be able to

• Critically examine, evaluate and compare Bayesian statistical models.

Main content of the course

• Bayesian inference theory
• Simulation methods
• Regression
• Models with latent variables
• Model checking
• Model choice.

Teaching methods

Teaching consists of lectures and computer exercises.

Students who have been admitted to and registered on a course have the right to receive tuition and/or supervision for the duration of the time period specified for the particular course to which they were accepted (see, the university's admission regulations (in Swedish)). After that, the right to receive tuition and/or supervision expires.

Examination methods

Written Examination, 5 credits (Code: A001)
Individual written examination

Project, 2.5 credits (Code: A002)
Individual written report and oral presentation

For students with a documented disability, the university may approve applications for adapted or other forms of examinations.

For further information, see the university's local examination regulations (in Swedish).

Grades

According to the Higher Education Ordinance, Chapter 6, Section 18, a grade is to be awarded on the completion of a course, unless otherwise prescribed by the university. The university may prescribe which grading system shall apply. The grade is to be determined by a teacher specifically appointed by the university (an examiner).

In accordance with university regulations regarding grading systems for first and second-cycle courses (Vice-Chancellor’s decision ORU 2018/00929), one of the following grades shall be used: Fail (U), Pass (G) or Pass with Distinction (VG). For courses that are included in an international Master’s programme (60 or 120 credits) or offered to the university’s incoming exchange students, the grading scale of A-F shall be used. The vice-chancellor, or a person appointed by the vice-chancellor, may decide on exceptions from this provision for a specific course, if there are special grounds.

Grades used on course are Fail (F), Sufficient (E), Satisfactory (D), Good (C), Very Good (B) or Excellent (A).

Written Examination
Grades used are Fail (F), Sufficient (E), Satisfactory (D), Good (C), Very Good (B) or Excellent (A).

Project
Grades used are Fail (F), Sufficient (E), Satisfactory (D), Good (C), Very Good (B) or Excellent (A).

For further information, see the university's local examination regulations (in Swedish).

Comments on grades

To obtain a passing grade for the course as a whole, a passing grade is required on all course components. The final grade for the entire course is a function of the grades of the course components. Detailed information on the requirements for different grade levels is given at the course start.

Specific entry requirements

First-cycle courses of 90 credits in statistics, including an independent project of 15 credits, alternatively 30 credits are for studies in statistics and 60 credits for mathematics, and where the courses Statistics, Statistical Theory, second cycle, 7.5 credits and Statistics, Computational Statistics are included. The applicant must also have qualifications corresponding to the course "English 6" or "English B" from the Swedish Upper Secondary School.

For further information, see the university's admission regulations (in Swedish).

Transfer of credits for previous studies

Students who have previously completed higher education or other activities are, in accordance with the Higher Education Ordinance, entitled to have these credited towards the current programme, providing that the previous studies or activities meet certain criteria.

For further information, see the university's local credit transfer regulations (in Swedish).

Reading list and other teaching materials

Required Reading

Gelman, Andrew et al. Third Edition
Bayesian Data Analysis
Chapman and Hall/CRC

Additional Reading
Albert, Jim 2009/2. ed.
Bayesian Computation with R
New York : Springer, 298 pages