M1100-CMS16
Statistical Principles and Experimental Design
|
|
|
|
| Module Owner: |
Prof.Dr. Ingo Röder |
| Displayed in timetable as: |
CMS-COR-SED |
| Duration: |
5 |
| Number of electives: |
0 |
| Credits: |
5,0
|
| Start Semester: |
WiSe 2018/19 |
| Lecturer Responsible |
Prof. Dr. M.D. Ingo Röder
ingo.roeder@tu-dresden.de
|
| Qualification Goals |
Upon completing the module, the students master the methodical and practical basics of statistical data analysis and modelling, as well as the planning of experiments. They are able to describe and analyse data using statistical methods and interpret their results correctly. Furthermore, they gain the ability to plan experiments in such a way that a subsequent data evaluation in the context of the respective question is meaningful and efficient. |
| Content |
Contents of the module are basic terms of probability theory (e.g. random variables, distributions, threshold sets), schools of statistical inference (e.g. frequentist, Bayesian, likelihood-based), estimation methods (e.g. point and interval estimators), principle and application statistical tests (e.g. significance and fit test), concept and application of statistical models (e.g. linear and generalized linear models), variance components and types, principles of experimental design (e.g. replication, randomisation, block formation), special designs (e.g. factorial designs, block designs), sample size planning. |
| Forms of Teaching and Learning |
The module includes 2 SWS worth of lectures, 2 SWS worth of exercises and the self-study. |
| Prerequisites for Participation |
Basic knowledge in the rudiments of probability calculus, analysis of functions of one and more variables, linear algebra (vector and matrix calculation), as well as basic knowledge of computer programming at the Bachelor's level.
Students can prepare for the module with the following literature:
Cormen, Leiserson, Rivest & Stein: Introduction to Algorithms, 2nd Edition, MIT Press 2001;
Hefferon, Jim: Linear Algebra, http://joshua.smcvt.edu/linearalgebra/, 2008;
Tamás Rudas: Handbook of Probability: Theory and Applications, Sage Publications, Inc., 2008 |
| Applicability |
In the Computational Modelling and Simulation Master's programme, the module is one of six compulsory elective modules of which three must be chosen. It cannot be selected by students of the Tracks Computational Life Science. This module is a compulsory module, within the Master's of Track Computational Science programme. |
| Prerequisites for the Assignment of Credit Points |
The credit points are awarded if the module examination is passed. If there are more than 10 registered students, the module examination consists of a written examination, with a duration of 90 minutes. If there are 10 or fewer registered students, it consists of an oral examination as an individual examination performance amounting to 30 minutes; this will be announced to the enrolled students at the end of the enrollment period. |
| Credit Points and Grades |
This module allows for the earning of 5 credit points.
The module grade corresponds to the grade of the examination performance. |
| Frequency of Offer |
The module is offered in each winter semester. |
| Workload |
The workload is a total of 150 hours. |
| Duration of Module |
The module takes one semester. |
| Module Number Module Handbook TU Dresden |
CMS-COR-SED |
