[ 551MASTSTIV14 ] VL Statistical Inference

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Workload Education level Study areas Responsible person Hours per week Coordinating university
5 ECTS B2 - Bachelor's programme 2. year Statistics Werner Müller 4 hpw Johannes Kepler University Linz
Detailed information
Pre-requisites (*)keine
Original study plan Bachelor's programme Statistics and Data Science 2021W
Objectives Students understand the techniques of Mathematical Statistics and have acquired the ability to apply these methods.
Subject Properties of a random sample, order statistics

Sufficiency, Likelihood principle, equivariance principle

Point estimation (ML, method of moments, Bayes estimator), criteria for point estimates, Cramer-Rao inequality

hypothesis testing: likelihood ratio test, Bayes-test, Lemma of Neyman and Pearson, p-values

intervall estimation: inversion of tests, Bayesian intervals, coverage, criteria for interval estimates

Criteria for evaluation Exam
Methods Lecture
Language German
Study material G. Casella and R.L. Berger, Statistical Inference. Robert Hafner, Wahrscheinlichkeitsrechnung und Statistik.
Changing subject? No
Corresponding lecture (*)4MSMS1V: VL Mathematische Statistik I (8 ECTS)
On-site course
Maximum number of participants 100
Assignment procedure Assignment according to priority