Courses: STAT210 Theory of Statistical Inference - Autumn 2017

English

Spring

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
of moments.
Be able to handle a parametric hypothesis testing problem and to use the likelihood ratio method.
Have some knowledge of asymptotic statistics.

MAT112 Calculus II, MAT121 Linear Algebra, and STAT111 Statistical Methods

Written examination, 5 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.

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