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The Statistics and Theory of Numerical Simulation

Module name (EN): The Statistics and Theory of Numerical Simulation
Degree programme: Engineering and Management, Master, ASPO 01.10.2019
Module code: MAM_19_A_1.01.MTS
SAP-Submodule-No.: P241-0088
Hours per semester week / Teaching method: 5V+3U (8 hours per week)
ECTS credits: 8
Semester: 1
Mandatory course: yes
Language of instruction:
Written exam 120 min.

[updated 04.11.2020]
Applicability / Curricular relevance:
DFMME-110 (P610-0443) Mechanical Engineering, Master, ASPO 01.10.2019, semester 1, mandatory course
MAM_19_A_1.01.MTS (P241-0088) Engineering and Management, Master, ASPO 01.10.2019, semester 1, mandatory course
120 class hours (= 90 clock hours) over a 15-week period.
The total student study time is 240 hours (equivalent to 8 ECTS credits).
There are therefore 150 hours available for class preparation and follow-up work and exam preparation.
Recommended prerequisites (modules):
Recommended as prerequisite for:
MAM. Experiment Design and Quality Control
MAM_19_M_3.03.ASF Applied Numerical Simulations (Fluid Mechanics / Heat Transport)
MAM_19_PE_2.04.SHY Hydraulic Servo-Motors

[updated 08.02.2022]
Module coordinator:
Prof. Dr. Marco Günther
Lecturer: Prof. Dr. Marco Günther

[updated 21.03.2019]
Learning outcomes:
After successfully completing this module, students will be able to solve statistical problems in the field of engineering sciences independently. They will be able to prepare and analyse complex data sets and interpret the results. Using suitable estimation methods, they will be able to draw conclusions about the population from a sample and critically scrutinize available statistics or the results of their evaluation.
Simulation Theory
In the context of engineering problems, students will be familiar with the basics of mathematical modeling and numerical methods. They will be familiar with the basic properties of partial differential equations, simple solution methods and know about the possibilities and limitations of numerical methods using the finite difference method.

[updated 04.11.2020]
Module content:
- Descriptive statistics: central tendencies and dispersion, correlation, regression
- Probability calculation: random variables und distributions, limit theorems
- Inferential statistics: point estimate, interval estimate, testing hypotheses
- Introduction to a statistics program package
Simulation Theory:
- Fundamentals of vector analysis (repetition)
- Fundamentals of partial differential equations (e.g. classification)
- Basic concepts of numerics like stability, convergence, error
- Solution methods: separable partial differential equation, Finite Differences Method (FDM)
- Applying the FDM to boundary value problems and initial boundary value problems
- Using Comsol Multiphysics as a solution tool

[updated 04.11.2020]
Teaching methods/Media:
Lecture: 3 hours per semester week, tutorials: 2 hours per semester week,  
Use of the web-based learning software ActiveMath:,
Simulation Theory:
Lecture: 2 hours per semester week, Tutorials: 1 hour per semester week,  
Blackboard, slides, handouts, tutorials

[updated 04.11.2020]
Recommended or required reading:
Weber H.: Einführung in die Wahrscheinlichkeit und Statistik für Ingenieure
Hartung J., Elpelt B.: Multivariate Statistik
Walz G., Grabowski B.: Lexikon der Stochastik mit Beispielen
Lecture notes _Deskriptive Statistik_, und Formelsammlung 1
Lecture notes _Wahrscheinlichkeitsrechnung_ und Formelsammlung 2
Simulation Theory:
Angermann A., Beuschel M, Rau M., Wohlfarth U.: MATLAB _ Simulink _ Stateflow
Knabner P., Angermann L.: Numerik partieller Differentialgleichungen

[updated 04.11.2020]
[Sun Aug 14 05:22:51 CEST 2022, CKEY=msutds, BKEY=mm2, CID=MAM_19_A_1.01.MTS, LANGUAGE=en, DATE=14.08.2022]