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[ 551MASTSTIU14 ] UE Statistical Inference
Versionsauswahl
(*) Unfortunately this information is not available in english.
Workload Education level Study areas Responsible person Hours per week Coordinating university
4 ECTS B2 - Bachelor's programme 2. year Statistics Werner Müller 2 hpw Johannes Kepler University Linz
Detailed information
Pre-requisites (*)keine
Original study plan Bachelor's programme Statistics and Data Science 2025W
Learning Outcomes
Competences
The courses VL and UE Statistische Inferenz form an inseparable didactic unit. The learning outcomes described below are achieved through the interaction of the two courses:

Students are able to mathematically justify and possibly improve methods of statistical inference.

Skills Knowledge
  • Knowing and understanding of the basic problems, concepts and procedures of statistical inference (k1,k2)
  • Classify the concepts in their historical and contemporary meaning (k1)
  • Derive mathematical facts and theorems (k3,k4,k5)
  • Use of the Mathematica program package (k3)
  • Properties of a random sample
  • Order statistics
  • Principles of data reduction (sufficiency, likelihood, equivariance)
  • Point estimation
  • Hypothesis testing
  • Interval estimators
  • Statistical methods in Mathematica
Criteria for evaluation homework
Methods discussion of the homework
Language German
Study material G. Casella and R.L. Berger, Statistical Inference. Robert Hafner, Wahrscheinlichkeitsrechnung und Statistik.
Changing subject? No
Corresponding lecture (*)4MSMS1U: UE Mathematische Statistik I (4 ECTS)
On-site course
Maximum number of participants 40
Assignment procedure Assignment according to priority