Main content
Elementary Probability and Statistics
(dt. Elementare Stochastik)
Level, degree of commitment | Advanced module, compulsory elective module |
Forms of teaching and learning, workload |
Lecture (4 SWS), recitation class (2 SWS) or lecture using videos (4 SWS), Repetitorium (2 SWS), recitation class (2 SWS), 270 hours (90 h attendance, 180 h private study or 60 h attendance and 210 h private study) |
Credit points, formal requirements |
9 CP Course requirement(s): Successful completion of at least 50 percent of the points from the weekly exercises. Examination type: Written or oral examination (individual examination) |
Language, Grading |
German,The grading is done with 0 to 15 points according to the examination regulations for the degree program B.Sc. Business Mathematics. |
Duration, frequency |
One semester, each winter semester |
Person in charge of the module's outline | Prof. Dr. Hajo Holzmann |
Contents
Basic concepts of probability theory
- Result space, events, discrete probability distributions, combinatorics.
- Conditional probability, independence, random variables, expected value, conditional expected value, variance, covariance, correlation, moments
- General probability spaces and random variables
- Stochastic convergence and laws of large numbers
- Convergence in distribution and the central limit theorem
- Basic concepts of statistics
- descriptive statistics and data types
- Elements of inferential statistics: statistical models, estimation, confidence intervals, hypothesis testing
Qualification Goals
Students will
- know the basic concepts of stochastics,
- have practiced the basics of modeling random quantities using probabilistic models,
- know basic principles of descriptive and inferential statistics,
- have practiced mathematical working methods (development of mathematical intuition and its formal justification, abstraction, proof),
- have improved their oral communication skills in exercises by practicing free speech in front of an audience and in discussion.
Prerequisites
None. The competences taught in the following modules are recommended: either Foundations of Mathematics and Linear Algebra I and Linear Algebra II or Basic Linear Algebra, either Analysis I and Analysis II or Basic Real Analysis.
Applicability
Module imported from B.Sc. Business Mathematics.
It can be attended at FB12 in study program(s)
- B.Sc. Data Science
- B.Sc. Mathematics
- B.Sc. Business Mathematics
- M.Sc. Computer Science
- M.Sc. Business Informatics
- BA Minor Mathematics
When studying M.Sc. Computer Science, this module can be attended in the study area Profile Area Mathematics.
Recommended Reading
- Henze, N. „Stochastik für Einsteiger“, 13. Auflage, Springer Spektrum , 2021
- Krengel, U. "Einführung in die Wahrscheinlichkeitstheorie und Statistik", 8. Auflage, Vieweg Studium, 2008
- Georgii, H. O. „Stochastik: Einführung in die Wahrscheinlichkeitstheorie und Statistik“, 4. Auflage. De Gruyter, 2009
Please note:
This page describes a module according to the latest valid module guide in Winter semester 2023/24. Most rules valid for a module are not covered by the examination regulations and can therefore be updated on a semesterly basis. The following versions are available in the online module guide:
- Winter 2016/17
- Summer 2018
- Winter 2018/19
- Winter 2019/20
- Winter 2020/21
- Summer 2021
- Winter 2021/22
- Winter 2022/23
- Winter 2023/24
The module guide contains all modules, independent of the current event offer. Please compare the current course catalogue in Marvin.
The information in this online module guide was created automatically. Legally binding is only the information in the examination regulations (Prüfungsordnung). If you notice any discrepancies or errors, we would be grateful for any advice.