Theory of Statistical Inference
- ECTS credits
- Teaching semesters
- Course code
- Number of semesters
Objectives and Content
The course will give the conceptual and mathematical basis for further studies of statistical methods at a theoretic level.
After completed course, the students are expected to:
- Know the most common distributions and the exponential family.
- Be familiar with transformation of univariate and multivariate densities.
- Know the concept of covariance and conditional probability.
- Know the different notions of convergence i statistics like
convergence in probability, almost sure convergence and convergence in distribution.
- Be familiar with the concept of sufficiency and the likelihood principle.
- Know the most important estimation methods like maximum likelihood, least square and the method
- Be able to handle a parametric hypothesis testing problem and to use the likelihood ratio method.
- Have some knowledge of asymptotic statistics.
Semester of Instruction
Required Previous Knowledge
Recommended Previous Knowledge
Compulsory Assignments and Attendance
Forms of Assessment
Written examination, 4 hours. Examination support materials: Non- programmable calculator, according to model listed in faculty regulations.
Examination only in the spring.
The grading scale used is A to F. Grade A is the highest passing grade in the grading scale, grade F is a fail.