ØAMET4200 Research Methods for Social Sciences Course description

The course particularly builds on a foundation course in social science research methods at bachelor's degree level and a foundation course in statistical methodology. This is a compulsory common course in the main profile Strategy, Organisation and Leadership.

No formal requirements over and above the admission requirements. Some knowledge of basic building physics at bachelor's degree level is an advantage.

After completing the course, students will acquired the learning outcomes defined in knowledge, skills and general competence

Knowledge

The student

• in-depth knowledge and understanding of how models are used in the social sciences

Skills

The student is capable of

• formulating issues and research questions, searching for relevant literature and applying theory in a reflected manner
• relating research questions and context to choice of method and analysing data to answer research questions
• planning and carrying out the empirical part of a master¿s thesis in the field of organisation and management
• carrying out an independent, limited research project in the form of a master's thesis in his/her field under supervision and in accordance with applicable research ethical standards;

The teaching consists of lectures, demonstration of measurement methods and simulations tools. In addition, a project assignment will be given in which the students are to perform analytical and simulation-based calculations of the performance of building components in connection with the different building physics phenomena.

The following required coursework must be approved before a student can take the exam:

1. Meet all deadlines for submission of all project parts (during the semester)
2. The project parts should be approved  

Students who fail to meet the coursework requirements can be given up to one re-submission opportunity before the exam.

Type of assessment:  

1) Project report in groups of 2-3 students (approx. 50-70 pages, excl. appendices), weighted 50%

2) Oral exam, individual or in group, weighted 50%

All assessment parts must be awarded a pass grade (E or better) in order for the student to pass the course.

Assessment parts: 1) may be appealed and 2) cannot be appealed.

All reference aids are allowed while working on the project description as long as the rules for source references are followed.

Written exam: No reference aids are allowed.

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.

1): one (or two) internal examiner(s).

2) Two examiners. 

External examiners are used regularly.

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