News
Knowledge requirements for participationWritten on 07.04.25 by Henryk Zähle Dear students, Thank you for your interest in the lecture course "Mathematical Statistics". Before the course starts, I would like to point out once again that the course is primarily aimed at students of the following three study programmes: - Mathematics Dear students, Thank you for your interest in the lecture course "Mathematical Statistics". Before the course starts, I would like to point out once again that the course is primarily aimed at students of the following three study programmes: - Mathematics For successful participation, a sound (!) knowledge of measure-theoretical stochastics, as taught e.g. in the mathematics courses "Stochastics 1" and "Stochastics 2", is required. Among other things, it is assumed that you are familiar with the following concepts: general probability spaces, (infinite) product measures and (infinite) product spaces, absolute continuity, general densities, random variables, expected value and (co-)variance, stochastic convergence concepts, strong and weak limit theorems (SLLN, CLT, ...), multivariate normal distribution, multivariate CLT, general conditional expectations, general conditional distributions (i.e. special probability kernels), etc. Best regards |
Lecturer: Prof. Dr. Henryk Zähle.
Assistent: Benedikt Flierl, MSc.
Please contact Benedikt Flierl (flierl[at]math.uni-sb.de) if you have any questions about this course.
Contents
The three basic concepts of statistical inference are
- point estimation,
- confidence regions,
- hypothesis testing.
In this lecture course, these three concepts are introduced and analysed on a sound mathematical level.
Recommended prerequisites
Stochastics I and II, and basic lectures in analysis and linear algebra (e.g. Analysis I-III, Linear Algebra I-II).
This course is intended for students of Mathematics or Actuarial and Financial Mathematics or Mathematics & Computer Science.
Participation in the course requires a basic education in mathematics and a sound knowledge in measure-theoretic probability theory (as taught in the courses Stochastics I and II).
Language
The course will be held in English unless all participants speak German.
Lectures
Tuesday, 8:30-10.00 am, in SR 6 (room 2.17) in building E2 4
Thursday, 8:30-10:00 am, in SR 6 (room 2.17) in building E2 4
Course materials are available here.
Tutorial
Wednesday, 8:30-10.00 am, in SR 6 (room 2.17) in building E2 4.
The first tutorial will take place on 23 April 2025.
Assignments
There will be weekly assignments, which will be uploaded on Thursdays. They are available here.
Submission via CMS one week later (by Thursday, 8:30 am).
The solutions will be discussed in the tutorials.
Exam
At the end of the term, there will be an oral exam.
To be admitted to the exam, you must achieve at least 50% of the total score of the assignments.