Örebro University School of Business

Course Syllabus

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)

Knowledge and understanding

After completing the course the student shall have
- knowledge of numerical methods and their limitations
- knowledge of common computationally intensive methods for statistical analysis.

Competence and skills

The should shall after completing the course be able to
- independently implement computational algorithms in the R programming language.

Judgement and approach

After completing the course the student has the ability to
- independently adapt and select an appropriate algorithm based on the requirements of the statistical issue
- independently seek new knowledge and judge its relevance for the statistical issue at hand
- independently design simulation studies for evaluating the statistical properties of a test or estimator.

- Floating point numbers and computer arithmetic
- Algorithms and basic programming in R
- Numerical linear algebra
- Numerical optimization
- Random number generators
- Simulation methids
- Numerical integration
- Bootstrap and Jackknife.

Lectures and computer labs.

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.

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

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).

According to regulations on grading systems for first- and second-cycle education (vice-chancellor's decision 2010-10-19, reg. no. CF 12-540/2010), one of the following grades is to be used: fail, pass, or pass with distinction. 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 reasons.

Grades used on course are Fail (U), Pass (G) or Pass with Distinction (VG).

Final Grade
For the concluding grade Pass on the course, a pass in both the written examination and assignments is required. For the grade Pass with Distinction, Pass with Distinction on the written examination and Pass on the assignments is required.

The final grade will be translated into the ECTS grading scale.

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

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, as well as the course Statistics, Statistical Theory, second cycle, 7.5 credits. 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).

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).

Required Reading

Gray, R. (2002)
Advanced Statistical Computing, Course notes
(online access at http://biowww.dfci.harvard.edu/~gray/248-02/report.pdf)

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