406-2604-AAL  Probability and Statistics

SemesterSpring Semester 2021
LecturersJ. Teichmann
Periodicityevery semester recurring course
Language of instructionEnglish
CommentEnrolment ONLY for MSc students with a decree declaring this course unit as an additional admission requirement.

Any other students (e.g. incoming exchange students, doctoral students) CANNOT enrol for this course unit.



Courses

NumberTitleHoursLecturers
406-2604-AA RProbability and Statistics
Self-study course. No presence required.
210s hrsJ. Teichmann

Catalogue data

Abstract- Statistical models
- Methods of moments
- Maximum likelihood estimation
- Hypothesis testing
- Confidence intervals
- Introductory Bayesian statistics
- Linear regression model
- Rudiments of high-dimensional statistics
ObjectiveThe goal of this part of the course is to provide a solid introduction into statistics. It offers of a wide overview of the main tools used in statistical inference. The course will start with an introduction to statistical models and end with some notions of high-dimensional statistics. Some time will be spent on proving certain important results. Tools from probability and measure theory will be assumed to be known and hence will be only and occasionally recalled.
Lecture notesScript of Prof. Dr. S. van de Geer
LiteratureThese references could be use complementary sources:

R. Berger and G. Casella, Statistical Inference
J. A. Rice, Mathematical Statistics and Data Analysis
L. Wasserman, All of Statistics

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits7 credits
ExaminersJ. Teichmann
Typesession examination
Language of examinationEnglish
RepetitionThe performance assessment is offered every session. Repetition possible without re-enrolling for the course unit.
Mode of examinationwritten 180 minutes
Written aidsCollection of formulas; precise format will be communicated in the course (Course 401-2604-00L Probability and Statistics (taught in the Spring Semester)) or on the course webpage.
This information can be updated until the beginning of the semester; information on the examination timetable is binding.

Learning materials

No public learning materials available.
Only public learning materials are listed.

Groups

No information on groups available.

Restrictions

There are no additional restrictions for the registration.

Offered in

ProgrammeSectionType
Mathematics MasterCourse Units for Additional Admission RequirementsE-Information
Statistics MasterCourse Units for Additional Admission RequirementsE-Information