Theory of Statistical Inference
- ECTS credits10
- Teaching semesterSpring
- Course codeSTAT210
- Number of semesters1
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.
Required Previous Knowledge
Recommended Previous Knowledge
MAT112 Calculus II, MAT121 Linear Algebra, and STAT111 Statistical Methods
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.
For written exams, please note that the start time may change from 09:00 to 15:00 or vice versa until 14 days prior to the exam.
Type of assessment: Written examination
- 05.06.2023, 15:00
- 4 hours
- Withdrawal deadline
- Examination system
- Digital exam