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Inference Theory

This course gives you an in-depth understanding of basic statistical principles, such as the principles of sufficiency, ancilliarity, invariance, and conditionality. Bayesian, likelihood-basedand Neyman-Pearson inference are applied and exemplified through point-estimation, interval estimation, and hypothesis testing.

You will learn about important theorems in inference theory and convergence-properties of estimators. You will also learn how to derive important point estimators, interval estimators, and test statistics in some selected applications.

The course provides a solid base for research studies in statistics.

  • Course structure

    The course is given at day time, full time.

    The course forms a part of the Master's Program in Statistics, but it can also be studied as a freestanding course.

    Teaching format

    The teaching forms consist of lectures and exercises.

    Language: English.

    Course Information

    More information for registered students will be found in Athena.


    Examination will be in the form of written and oral examination.

  • Course literature

    Note that the course literature can be changed up to two months before the start of the course.