Syllabus for Introductory Statistics
Grundläggande statistik A4
- 15 credits
- Course code: 2ST063
- Education cycle: First cycle
Main field(s) of study and in-depth level:
Explanation of codes
The code indicates the education cycle and in-depth level of the course in relation to other courses within the same main field of study according to the requirements for general degrees:
- G1N: has only upper-secondary level entry requirements
- G1F: has less than 60 credits in first-cycle course/s as entry requirements
- G1E: contains specially designed degree project for Higher Education Diploma
- G2F: has at least 60 credits in first-cycle course/s as entry requirements
- G2E: has at least 60 credits in first-cycle course/s as entry requirements, contains degree project for Bachelor of Arts/Bachelor of Science
- GXX: in-depth level of the course cannot be classified
- A1N: has only first-cycle course/s as entry requirements
- A1F: has second-cycle course/s as entry requirements
- A1E: contains degree project for Master of Arts/Master of Science (60 credits)
- A2E: contains degree project for Master of Arts/Master of Science (120 credits)
- AXX: in-depth level of the course cannot be classified
- Grading system: Fail (U), Pass (G), Pass with distinction (VG)
- Established: 2007-01-22
- Established by:
- Revised: 2020-03-27
- Revised by: The Department Board
- Applies from: Autumn 2022
- Entry requirements: General entry requirements and Mathematics 3b or 3c/Mathematics C, Social Studies 1b or 1a1+1a2
- Responsible department: Department of Statistics
After completing the course, a student is expected to:
- have knowledge about basic concepts in statistics
- have basic theoretical knowledge in probability theory and statistical inference
- own ability to apply statistical methods for collection, processing and analysis of quantitative and qualitative data particularly such linked to the field of economy, business and social science
- be able to critically review research reports and conclusions based on statistical data
- be able to present results of statistical studies
- be able to use standard statistical software.
Graphical descriptive methods and numerical descriptive measures. Data collection and sampling methods. Elementary probability theory, discrete and continuous probability distributions. Sampling distributions. Point estimation and confidence intervals. Parametric and non-parametric hypothesis tests. Analysis of relationships between variables, correlation and simple linear regression. Time Series.
Instruction is given in the form of lectures, supplementary lectures, and computer introduction.
The examination takes place both through a written exam at the end of the course and through a number of compulsory assignments. A more detailed description of the compulsory assignments can be found in the course description for a specific semester.
If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the University's disability coordinator.
The course cannot be included in a degree where the course Statistics for Economics A8 is included.
- Latest syllabus (applies from Autumn 2022)
- Previous syllabus (applies from Spring 2020)
- Previous syllabus (applies from Autumn 2019)
- Previous syllabus (applies from Spring 2017)
- Previous syllabus (applies from Autumn 2013)
- Previous syllabus (applies from Autumn 2010, version 2)
- Previous syllabus (applies from Autumn 2010, version 1)
- Previous syllabus (applies from Spring 2010)
- Previous syllabus (applies from Autumn 2007)
The reading list is missing. For further information, please contact the responsible department.