Data Science

Knowledge

• recognize the challenges with respect to data collection, data quality, and alignment between research questions and the data
• recognize descriptive statistics as basic summaries of specific data features
• recognize that sampling variability and uncertainty are ubiquitous

Skills

• run basic data management, visualization, and analysis techniques using the open source statistical software environment R

Competence

• manage a core dataset by wrangling it into shape for specific data-analyses and performing an audit to document and clean unexpected irregularities
• visualize data paying attention to basic quality criteria to increase clarity and communication value
• perform and communicate basic data analyses taking into consideration features of the study design and inferential uncertainty

Students who are admitted to study programmes at UiO must each semester register which courses and exams they wish to sign up for in Studentweb.

If you are not already enrolled as a student at UiO, please see our information about admission requirements and procedures.

This course is a compulsory part of the master's programme Assessment, Measurement and Evaluation. Students on exchange on master's level at UiO or enrolled in other UiO master's programmes may be given admission based on availability. Contact [email protected] with your request to attend the course.

PhD candidates can apply to the PhD version of the course: UV9290

This course combines lectures and computer labs with data analysis tasks in statistical software environments.

Obligatory course components:

• Attendance in the first lecture
• 80% attendance requirement for the lectures
• A diverse set of small and moderate assignments is used to keep track of student progress throughout the course.

The learning management system CANVAS is used for providing detailed information about requirements and deadlines for assignments.

Successful completion of each assignment is a prerequisite for being allowed to submit the final portfolio exam. Exam qualifying requirements need to be met in one and the same year. Once qualified for participating in the exam, you retain this qualification for the next two times the course is offered.

The portfolio exam consists of three components:

1. Data wrangling and auditing component
2. Data visualization product and critique component
3. Data report component

The delivery of each exam component will take the form of a brief report comprising the R code and related output based on an individualized dataset.

Each exam component counts for one third of the final grade and you need to pass on each component to be able to pass the exam.

You have to pass all three exam components in the same semester for the exam result to be valid.

You need to have successfully completed the obligatory course components before being allowed to sit the exam.

This course will use the new exam system at UiO "WISEflow" as a pilot autumn 2026.»

Previously given exams and grading guides

You are allowed to bring and consult your own "cheat sheet". The cheat sheet can contain whatever course contents you find useful for yourself, but the sheet does need to fulfill the following requirements:

• 1 page A4-format
• Hand-written contents
• Inside a plastic cover

You can write on both sides of the sheet of paper. Anything outside the requirements (e.g., a typed page, 2,5 pages or even a copy of the original), is not be permitted and will be taken away.

• Illness at exams / postponed exams
• Resitting an examination