Fundamentals of Mathematical Statistics

What it is about

You will learn the fundamental principles and methods of statistical inference, including likelihood approaches, Bayesian methods and minimax estimation. You will deal with asymptotic theory for large samples and apply it in particular to the study and application of maximum-likelihood techniques.

What you will be able to do

Understanding the theoretical foundations of statistical inference
Knowledge and application of maximum-likelihood methods
Deriving asymptotic properties of estimators and tests
Applying statistical methods for parameter estimation and hypothesis testing in concrete models

What the module consists of

LecturePresentation of content with examples and discussion to convey the theory
Exercise/LabDeepening through exercises and solutions for self-check and application

Teaching method

LectureDelivery of content through lecture, demonstrative examples and discussion
ExercisesOffer of problem sheets and solutions for deepening and self-assessment

Dates

LectureFundamentals of Mathematical Statistics [MA5441]2 groups to choose from

AThu12:15–13:45
019, LMU Hörsaal im Physik Werkstattgebäude (5123.EG.019)
14× · 15.10.–04.02.
- 15.10.
- 22.10.
- 29.10.
- 05.11.
- 12.11.
- 19.11.
- 26.11.
- 10.12.
- 17.12.
- 07.01.
- 14.01.
- 21.01.
- 28.01.
- 04.02.
BMon12:15–13:45
003, Hörsaal 2, "Interims II" (5416.01.003)
15× · 12.10.–01.02.
- 12.10.
- 19.10.
- 26.10.
- 02.11.
- 09.11.
- 16.11.
- 23.11.
- 30.11.
- 07.12.
- 14.12.
- 21.12.
- 11.01.
- 18.01.
- 25.01.
- 01.02.

From the current semester, not binding. You attend one of several groups; the timetable automatically suggests the one with the fewest clashes.

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