Workload:
180 h
|
Module Number INF2021 (BIOINFM2021) |
Module Title Mathematics for Computer Science 4: Stochastics (Stochastics) |
Type of Module Compulsory |
|---|---|---|
| ECTS | 6 | |
|
Work load - Contact time - Self study |
Workload:
180 h Class time:
60 h / 4 SWS Self study:
120 h |
|
| Duration | 1 Semester | |
| Frequency | In the summer semester | |
| Language of instruction | German | |
| Type of Exam | Written Test |
|
| Lecture type(s) | Lecture, Tutorial | |
| Content | Topics include probability spaces, random variables, distributions, Independence, Law of Large Numbers, Central Limit Theorem, Stochastic Processes, Stochastic Models, Sampling, and Estimating & Testing. |
|
| Objectives | Students receive basic knowledge in probability theory and statistics. They are able to describe and analyze simple random phenomena mathematically. They are able to apply basic stochastic methods in computer science (e.g. bioinformatics, randomized algorithms). |
|
| Allocation of credits / grading |
Type of Class
Status
SWS
Credits
Type of Exam
Exam duration
Evaluation
Calculation
of Module (%)
Lecture
V
o
2
4.0
wt
90
g
100
Tutorial
Ü
o
2
1.0
|
|
| Prerequisite for participation |
INFM1010 Mathematics for Computer Science 1: Analysis, INFM1020 Mathematics for Computer Science 2: Linear Algebra |
|
| Lecturer / Other | Teufl | |
| Literature | Georgii, H.-O.: Stochastik, de Gruyter; Krengel, U.: Einführung in die Wahrscheinlichkeitstheorie und Statistik, Vieweg; Wolff, M., Hauck, P. und Küchlin, W.: Mathematik für Informatik und Bioinformatik, Springer |
|
| Last offered | Sommersemester 2022 | |
| Planned for | Sommersemester 2025 | |
| Assigned Study Areas | BIOINFM, INFM2020, MDZINFM2510, MEINFM3210 | |