KIUA1004 Probability and Statistics

    • Number of credits
      10
    • Teaching semester
      2024 Autumn
    • Language of instruction
      Norwegian/English
    • Campus
      Hamar
    • Required prerequisite knowledge

      None.

Course content

Probability and Statistics will provide students with fundamental knowledge of and skills in probability theory and statistical analysis. Students will gain a deep understanding of probability concepts, including random variables and Bayesian statistics, and will develop excellent abilities to use statistical analysis techniques to test hypotheses and conduct regression analyses. This course is important to AI practitioners and enables them to make data-driven decisions, build predictive models and effectively apply statistical techniques in real-world AI applications.

Learning Outcome

Upon successfully passing the course, students will have achieved the following learning outcomes:

Knowledge

The student will have

  • a comprehensive understanding of the fundamental concepts of probability theory, including probability axioms, conditional probability and independence
  • knowledge of different probability distributions, including discrete distributions (e.g. binomial, Poisson) and continuous distributions (e.g. normal, exponential)
  • knowledge of statistical inference, including hypothesis testing, confidence intervals and types of errors
Skills

  • The student will be able to

  • analyse and interpret data using statistical techniques to apply exploratory data analysis, calculate descriptive statistics and visualise data in order to gain insights
  • use statistical software tools for data manipulation, basic statistical analysis and visualisation to perform statistical calculations and generate meaningful visual representations of data
  • build statistical models and draw conclusions from data to apply estimation techniques, perform hypothesis tests and interpret results in different contexts
General competence

The student will be able to

  • apply statistical concepts and techniques to real-world problems
  • utilise numerical literacy skills to work with statistical data, perform calculations and interpret numerical results that develop a strong understanding of quantitative information
  • communicate statistical findings and gain an insight into both technical and non-technical target groups
  • exercise an understanding of the ethical considerations linked to data collection, analysis and interpretation
Teaching and working methods

The course comprises a combination of lectures, practical exercises, independent study and academic supervision.

Required coursework
  • Two individual assignments in accordance with the course curriculum
  • Participation in teaching and laboratory exercises in accordance with the course curriculum

Compulsory coursework requirements that have been passed are valid for 12 months only. Students wishing to take examinations after 12 months must pass the compulsory coursework requirements again in connection with the next scheduled delivery of the course. 

Form of assessment
  • One four-hour individual written examination

 

The assignment is assessed using a grading scale from A-F, where E is the lowest passing grade.

Students are able to choose which language to use for their examination. The available options are Norwegian Bokmål, Nynorsk and English.

 

Permitted aids:

None

Assessments
Form of assessmentGrading scaleGroupingDuration of assessmentSupport materialsProportionComment
Written examination with invigilation
ECTS - A-F
Individual
4 Hour(s)
  • No support materials
100

Reading list

Faculty
Faculty of Audiovisual Media and Creative Technologies
Department
Department of Game Development - The Game School