Inference
Syllabus, Master's level, 2ST120
- Code
- 2ST120
- Education cycle
- Second cycle
- Main field(s) of study and in-depth level
- Statistics A1N
- Grading system
- Fail (U), Pass (G), Pass with distinction (VG)
- Finalised by
- The Department Board, 14 October 2022
- Responsible department
- Department of Statistics
Entry requirements
120 credits including 90 credits in statistics, or 120 credits including 60 credits in statistics and 30 credits in mathematics and/or computer science
Learning outcomes
After completing the course the student is expected to
- be familiar with and understand the basic principles of estimation
- be familiar with and understand the basic principles of testing
- be familiar with and understand the basic principles of confidence intervals.
Content
Method of moments, method of maximum likelihood, the invariance principle, consistency and unbiasedness, likelihood ratio tests, LM (score) and Wald tests, significance level and power function, properties of tests, interval estimation.
Instruction
Instruction is given in form of lectures.
Assessment
The examination takes place partly through a written examination at the end of the course and/or through presentation orally and in written form of compulsory assignments.
"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."