Jedes Modul umfasst 3 ECTS. Sie wählen insgesamt 10 Module/30 ECTS in den folgenden Modulkategorien:
- 12-15 ECTS in Technisch-wissenschaftlichen Modulen (TSM)
TSM-Module vermitteln Ihnen profilspezifische Fachkompetenz und ergänzen die dezentralen Vertiefungsmodule. - 9-12 ECTS in Erweiterten theoretischen Grundlagen (FTP)
FTP-Module behandeln theoretische Grundlagen wie die höhere Mathematik, Physik, Informationstheorie, Chemie usw. Sie erweitern Ihre abstrakte, wissenschaftliche Tiefe und tragen dazu bei, den für die Innovation wichtigen Bogen zwischen Abstraktion und Anwendung spannen zu können. - 6-9 ECTS in Kontextmodulen (CM)
CM-Module vermitteln Ihnen Zusatzkompetenzen aus Bereichen wie Technologiemanagement, Betriebswirtschaft, Kommunikation, Projektmanagement, Patentrecht, Vertragsrecht usw.
In der Modulbeschreibung (siehe: Herunterladen der vollständigen Modulbeschreibung) finden Sie die kompletten Sprachangaben je Modul, unterteilt in die folgenden Kategorien:
- Unterricht
- Dokumentation
- Prüfung
Students are introduced to statistical tools used in the industrial sector, and particularly in process and quality control. In this module, students learn to plan and conduct statistical evaluations independently.
Please note: An MSE cursus may not contain both similar statistics modules FTP_AppStat and FTP_PredMod. Students can only choose one of these modules.
Eintrittskompetenzen
Basic knowledge of the calculation of probabilities and statistics: models; parameter estimation; knowledge of how statistical tests are compiled and what confidence intervals are; user knowledge of a statistical program (Excel, R, S-PLUS, SPSS or MATLAB); fundamental laboratory experience (measuring technology)
Lernziele
To be in a position to plan and evaluate experiments in an industrial environment; understand how processes are statistically controlled and improved; be capable of analyzing and interpreting data by means of regression analysis; be able to implement the methods covered with a statistical package.
Modulinhalt
Statistical process and quality control (SPC): the "Magnificent Seven“, control charts, operating characteristic curve, acceptance sampling (weighting 1/3)
Introduction to multiple regression analysis: model prerequisites, confidence and prediction intervals, graphic checking of model assumptions (weighting 1/3)
Overview of Design of Experiment – DoE (planning and evaluating experiments): basic principles for the planning of experimental studies, one-way and multi-way analysis of variance, factorial experiment designs and their analysis, block designs (weighting 1/3)
The contents listed are illustrated with case studies from the industrial and scientific environment. In doing so, use is made of graphical methods and statistical bases, including classic and robust estimation methods and Monte Carlo simulations.
Lehr- und Lernmethoden
Lectures, practical work on the computer with a statistics program
Bibliografie
Lecturers' scripts with references to current literature
Vollständige Modulbeschreibung herunterladen
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