Programplaner og emneplaner - Student
SMUA4300 Advanced Research Methods Course description
- Course name in Norwegian
- Advanced Research Methods
- Weight
- 5.0 ECTS
- Year of study
- 2026/2027
- Course history
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- Curriculum
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FALL 2026
- Schedule
- Programme description
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Introduction
Much of the work in students´ scientific or practical work both during their studies and later in their professional life will require a good understanding of research methods and analytical tools and techniques. This course will provide the knowledge and skills necessary for planning and conducting engineering research, for processing data and for analysing results, with special focus upon the most common statistical techniques.
Language of Instruction: English
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Recommended preliminary courses
None
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Required preliminary courses
None.
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Learning outcomes
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 has advanced knowledge of:
- research methods, especially in engineering research
- statistical and analytical techniques, including knowledge of the most common methods used in statistical analysis and visualisation of the results
- designing experiments, formulating research questions, preparing data and interpreting analysis results
- how relevant statistical techniques relate to each other and where they are used
Skills:
The student has:
- required skills in setting up sound hypotheses and research questions, and in finding and preparing relevant data
- required skills in identifying which statistical and analytical techniques are to be used and how and where they should be used
- hands-on experience with some of the most common tools for statistical analysis
General competence:
The student:
- has broad overview of computational tools and techniques used in statistical analysis relevant for engineering and planning
- has an overview of the terminology related to statistical analysis and data science.
- is able to design experiments for successful engineering research, analyses and critical interpretation of results
- can extend his/her knowledge and skills in programming/scripting, analysing, managing and visualizing data
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Teaching and learning methods
This course features lectures and labs that provide both theoretical and practical content and hands-on experience.
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Course requirements
The following coursework requirements must be approved in order for the student to take the exam:
- one mandatory homework in allocated time and get it approved.
Students who fail to meet the coursework requirements can be given up to one re-submission opportunity. (more details in Canvas).
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Assessment
Individual written exam under supervision (4 hours)
The exam can be appealed.
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Permitted exam materials and equipment
Textbook, syllabus and own notes are permitted aids.
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Grading scale
Grade scale A to F.
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Examiners
Two internal examiners.
External examiners are used regularly.
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Course contact person
Hanna Vangen og Kristin Aarland