M. Eng. Wood Technology / Holztechnik - Hochschule für Architektur ...

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Master Wood Technology Module Catalogue / Modulhandbuch Module MG 02 – Statistics (compulsory module) Module coordinator Modulverantwortlicher Lecturers/tutors Referenten Location / term Durchführung des Moduls Credit Points (ECTS) 5 Number of lectures Anzahl der Vorlesungen Total workload Distribution of the hours Gesamtworkload Aufteilung der Stunden Pre-requisites for the module Modulvoraussetzungen Learning objectives Lernziele Contents Inhalt Teaching methods Lehrmethode Professor Dr. Ulrich Wellisch Tel.: +49 (0)8031 805 425 Email: ulrich.wellisch@fh-rosenheim.de Assistant Lecturer Dr. Haindl at the University Rosenheim in the winter term up to max. 30 participants 4 contact hours/week of seminar-type teaching 150 hours, of which � 60 contact hours � 90 hours preparation and follow-up work at home, exam preparation Admittance to the Master Programme of Wood Technology Identify stochastic statistical aspects in every-day processes and issues, especially in technical and economic processes and issues. Gain a broad overview of basic descriptive and explorative methods of statistical data analysis and the possibilities resp. limits of its application. Acquire the foundations of probability theory and application of central inductive statistical methods. Be able to perform independently data analysis and to apply statistical methods using current statistics software (R). Knowledge and integration of the functionalities and features of popular statistics software packages. Gain the ability to independently acquire stochastic statistical methods, to evaluate them critically and to implement them in practice using statistics software. I. Applied Statistics � introduction � descriptive statistics � univariate analysis � multivariate analysis � inductive statistics � point estimation � interval estimation � testing of hypotheses � linear model II. Principles of probability calculus III. Statistics software: Introduction to data analysis with R IV. Tutorial assignments � theory and methods � statistics software (R) The acquisition of the theoretical subject-matter and the use of the statistics software R are fostered by appropriate tutorial assignments. Seite 6
Master Wood Technology Module Catalogue / Modulhandbuch Teaching language Unterrichtssprache Examinations Prüfungsleistung & Leistungsbewertung Resources during the exam Hilfsmittel in der Prüfung Literature / reading list Literatur Observations Bemerkungen English written exam (90 min) one DIN A4 page, handwritten on both sides pocket calculator � Fahrmeir, L., Künstler, R., Pigeot, I., Tutz, G. (2003), Statistik Der Weg zur Datenanalyse, Springer Berlin. � Ligges, U. (2007), Programmieren mit R, Springer Berlin. � Pruscha, H. (2006), Statistisches Methodenbuch Verfahren, case studies, Programmcodes, Springer, Berlin. � Sachs,L., Hedderich, J. (2006), Angewandte Statistik Methodensammlung mit R, Springer Berlin. � Tukey, J. (1977), Exploratory Data Analysis, Addison-Wesley Reading Massachusetts. The statistical data analysis and the underlying stochastic modeling of processes have become a standard application in many areas of technology, science and economy. This development has been strongly encouraged by the wide availability nowadays of corresponding computer technology (hardware and software). The applications of statistical methods in data analysis vary from fundamental descriptive and explorative methods (e.g. possibilities of graphical representation of data) to highly-developed inductive methods (e.g. hypothesis tests or non parametrical regression methods). An efficient representation of data by means of different indices (e.g. for location and variation) and graphical means can for example yield insights into the data structure of test results. Using inductive statistical methods (e.g. correlation analysis and regression analysis or significance test) it is possible to draw statistically founded conclusions and for example decide whether an effect is statistically significant or whether a purely random behaviour has been observed. Knowledge of the various statistical methods is fundamental for the adequate planning of empirical trials (e.g. test planning). Fundamental knowledge of probability calculus is required in particular to deal adequately with inductive statistical methods. The practical application of statistical methods occurs by using suitable software. Standard methods have already been implemented nowadays in widely-available standard software (e.g. MS-Excel) but highly developped special statistics software packages have meanwhile also become available to everyone for free as open source software (e.g. R). An introduction to the statistics package R constitutes part of this lecture. Seite 7
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M. Eng. Wood Technology / Holztechnik - Hochschule für Architektur ...

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