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Statistical Inference

  • 7.5 credits

The aim of the course is to give a theoretical base of statistical inference. Concepts such as sufficiency, ancillary, invariance, the conditionality principle and likelihood ratios are treated in a rigorous way. Bayesian, likelihood and Neyman-Pearson inferences are applied and illustrated in point estimation, interval estimation and model choice. The course provides a solid base for research studies in statistics.

Further course information will appear soon on this page. Until then, information can be found on the department website.

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