M1100-CMS116
Statistical Principles and Experimental Design
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| Module Owner: |
Prof. Dr. Ingo Röder |
| Displayed in timetable as: |
CMS-COR-SED |
| Duration: |
7 |
| Number of electives: |
0 |
| Credits: |
5,0
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| Start Semester: |
WiSe 2020/21 |
| Lecturer Responsible |
Prof. Dr. med. 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 |
Content of the module include basic concepts of probability theory (e.g. random variables, distributions, limit sets), schools of statistical inference (e.g. frequentistic Bayesian, likelihood-based), estimation methods (e.g. point and interval estimators), principal and application of statistical tests (e.g. significance and fit test), term and application of statistical models (e.g. linear and generalised linear models), principles of experimental design (e.g. replication, randomisation, block formation), variance components and types, special designs (e.g. factorial designs, block designs), and aspects of sample size planning. |
| Forms of Teaching and Learning |
The module includes 2 weekly lectures, 2 weekly practicals and independent study. |
| Prerequisites for Participation |
Basic knowledge in the fundamentals of probability theory, analysis of functions of one or more variables, linear algebra (vector and matrix calculus) as well as basic knowledge of computer programming at bachelor level are required. Students can prepare for the module with the following literature:
Rohatgi & Saleh: An Introduction to Probability and Statistics, Wiley, 2001
Hefferon: 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 ten compulsory elective modules (for students of Computational Life Science: nine), of which three must be chosen. However, it cannot be chosen as a compulsory elective module by students of the Track Computational Life Science as it is a compulsory module. |
| Prerequisites for the Assignment of Credit Points |
The credit points are awarded if the module examination is passed.
The preliminary examination involves 9 practice tests of 12 (75 %).
The module examination itself consists of an examination paper lasting 90 minutes. If there are fewer than 10 students registered at the end of the registration period, the written examination can be replaced by an oral examination as individual examination lasting 30 minutes; if this is the case, this will be announced to the registered students at the end of the registration period. |
| Credit Points and Grades |
5 credit points can be earned by completing the module. The module grade corresponds to that of the graded work. |
| Frequency of Offer |
The module is offered every winter semester. |
| Workload |
The total workload is 150 hours. |
| Duration of Module |
The module takes one semester to complete. |
| Module Number Module Handbook TU Dresden |
CMS-COR-SED |
