MEK2200 Statistics and Risk Management Course description

The course includes training in statistical methods used for the processing of measurement data, handling sources of error, calculating probability and estimating measurement uncertainty. Furthermore, an introduction will be provided into regression analysis and methods for calibration and quantification, hypothesis testing and variance analysis. Emphasis will be placed on showing the application of statistical theory through examples and statistical problems. The course also includes definitions and discussions of basic concepts in risk management. The course gives the students basic knowledge and an understanding of quality control and quality assurance through, amongst other things, the application of knowledge acquired in statistics and risk management.

The student must have been admitted to the Master’s Programme in Health Sciences - Specialisation in Rehabilitation and Habilitation.

After completing the course, the student is expected to have achieved the following learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge

The student is capable of explaining:

• probability, probability calculation and probability distribution
• basic statistical processing of measurement data
• confidence and significance, confidence intervals and hypothesis testing, variance analysis
• errors and uncertainty, error accumulation and uncertainty estimates
• calibration and calibration curves
• what a risk assessment is, how a risk assessment is conducted, common methods used and how risk assessment is used in risk management
• quality control and quality assessment principles

Skills The student is capable of:

• assessing uncertainty and sources of error in measurement results
• using statistical methods to interpret and quality check measurement results
• performing risk assessments of various problems and interpreting and presenting the results of the analysis as a contribution to decisions concerning risk and quality

General competence The student:

• has basic insight into quality assessments and requirements
• has knowledge of how accuracy and precision in measurement results are affected by sources of error and uncertainty in instrumentation, procedures and work techniques
• has insight into statistical methods for the processing and interpretation of measurement data
• has a basic understanding of ethical issues relating to risk assessment, the use of risk acceptance criteria and how risk assessments can be used and abused

The teaching will mainly consist of lectures, exercises and laboratory assignments.

Project examination in the form of a written work that is developed during the course. The work is carried out individually with a scope of 2,000-2,500 words or in pairs with a scope of 3,500-4,000 words. The students will develop a research topic in consultation with the course lecturers.

Resit examination: If the student is awarded the grade F (fails the written assignment), he/she will be given one (1) opportunity to submit a reworked version.

All aids are permitted, as long as the rules for source referencing are complied with.

Grade scale A-F.

At least 20% of the examination papers will be assessed by an external examiner together with an internal examiner. The remaining papers will be assessed by two internal examiners. The external examiner’s assessment should benefit all students.

10 ECTS credits overlapp with MAREH4000 Rehabilitation as Knowledge and Practice, 20 ECTS credits. 

The course has an overlap of 10 credits with KJFP2200, MATS2200 and ELFE2600.

The course has an overlap of 5 credits with KJTF2311 and KJTF2310.

Under the rule that students have three attempts to take an exam, attempts in equivalent courses also count.