Suchergebnis: Katalogdaten im Frühjahrssemester 2020

Doktorat Departement Maschinenbau und Verfahrenstechnik Information
Mehr Informationen unter: Link
Lehrangebot Doktorat und Postdoktorat
NummerTitelTypECTSUmfangDozierende
151-0111-00LResearch Seminar in Fluid Dynamics
Internes Forschungsseminar für Doktoranden und wissenschaftliche Mitarbeiter des IFD.
Z0 KP2SP. Jenny, T. Rösgen
KurzbeschreibungCurrent research projects at the Institute of Fluid Dynamics are presented and discussed.
LernzielExchange on current internal research projects. Training of presentation skills.
InhaltCurrent research projects in Fluid Dynamics
» Auswahl aus sämtlichen Lehrveranstaltungen der ETH Zürich
151-0906-00LFrontiers in Energy Research Information
This course is only for doctoral students.
W2 KP2SC. Schaffner
KurzbeschreibungDoctoral students at ETH Zurich working in the broad area of energy present their research to their colleagues, their advisors and the scientific community. Each week a different student gives a 50-60 min presentation of their research (a full introduction, background & findings) followed by discussion with the audience.
LernzielThe key objectives of the course are:
(1) participants will gain knowledge of advanced research in the area of energy;
(2) participants will actively participate in discussion after each presentation;
(3) participants gain experience of different presentation styles;
(4) to create a network amongst the energy research doctoral student community.
InhaltDoctoral students at ETH Zurich working in the broad area of energy present their research to their colleagues, to their advisors and to the scientific community. There will be one presentation a week during the semester, each structured as follows: 20 min introduction to the research topic, 30 min presentation of the results, 30 min discussion with the audience.
SkriptSlides will be available on the Energy Science Center pages(Link).
151-0528-00LTheory of Phase TransitionsW4 KP3GL. Guin, D. Kochmann
KurzbeschreibungPhase transitions are responsible for various intriguing phenomena in physics and especially mechanics such as, e.g., superelasticity and the shape memory effect in shape memory alloys, polarization reversal in ferroelectrics, or dendritic solidification in crystal growth. This course surveys different theoretical approaches to phase transistions and introduces related modeling techniques.
LernzielStudents learn different approaches to describing phase transitions at the continuum scale (including the sharp-interface approach, regularized and phase-field models) and at the discrete level (e.g., chains of interacting particles). By discussing various physical problems involving phase transitions, while pointing out their common features and specific properties, students acquire a physical understanding of those phenomena. In addition, students learn basic concepts of modeling and numerically simulating problems involving phase transitions.
Inhalt1. Introduction - review of continuum mechanics and thermodynamics.
2. Stability of equilibria, the Ericksen's bar problem.
3. Equilibrium phase mixtures and quasistatic processes in 1D.
4. Continuum theory of phase boundaries in 3D.
5. Mathematical aspects of phase transitions.
6. A discrete approach with an atomistic basis.
7. Regularized and phase-field models.
8. Polarization switching in ferroelectrics: the Ginzburg-Landau theory.
9. Phase-field modeling of polarization switching.
10. Fourier-based methods for phase-field models.
11. Propagation of solidification fronts: the Stefan problem.
12. Crystal growth on vicinal surfaces.
13. The framework of configurational forces.
14. Phase transitions in metamaterials.
SkriptCopies of the lecture notes will be provided for each class, however students are strongly encouraged to take their own notes.
LiteraturEvolution of Phase Transitions: A Continuum Theory, R. Abeyaratne & J.K. Knwoles, Cambridge University Press
The Classical Stefan Problem, S.C. Gupta, Elsevier (recommended/not required background literature)
Voraussetzungen / BesonderesMechanics 1, 2 and 3. Ideally Continuum Mechanics.
151-0540-00LExperimentelle Mechanik
Findet dieses Semester nicht statt.
W4 KP2V + 1UJ. Dual
Kurzbeschreibung1. Allgemeines: Messkette, Frequenzgang, Schwingungen und Wellen in kontinuierlichen Systemen, Modalanalyse, Statistik, Digitale Signalanalyse, Phasenregelkreis 2. Optische Methoden 3. Piezoelektrizität 4. Elektromagnetische Erzeugung und Messung von Schwingungen und Wellen 5. Kapazitive Messaufnehmer
LernzielVerständnis, quantitative Modellierung und praktische Anwendung von experimentellen Methoden zur Erzeugung und Messung von mechanischen Grössen (Bewegung, Deformation, Spannungen)
Inhalt1. Allgemeines: Messkette, Frequenzgang, Frequenzgangmessung, Schwingungen und Wellen in kontinuierlichen Systemen, Modalanalyse, Statistik, Digitale Signalanalyse, Phasenregelkreis 2. Optische Methoden (Akustooptische Modulation, Interferometrie, Holographie, Spannungsoptik, Schattenoptik, Moiré Methoden) 3. Piezoelektrische Materialien: Grundgleichungen, Anwendungen Beschleunigungsaufnehmer, Verschiebungsmessung) 4. Elektromagnetische Erzeugung und Messung von Schwingungen und Wellen 5. Kapazitive Messaufnehmer, Praktika und Uebungen
Skriptja
Voraussetzungen / BesonderesVoraussetzungen: Mechanik I bis III, Physik, Elektrotechnik
151-0566-00LRecursive Estimation Information W4 KP2V + 1UR. D'Andrea
KurzbeschreibungEstimation of the state of a dynamic system based on a model and observations in a computationally efficient way.
LernzielLearn the basic recursive estimation methods and their underlying principles.
InhaltIntroduction to state estimation; probability review; Bayes' theorem; Bayesian tracking; extracting estimates from probability distributions; Kalman filter; extended Kalman filter; particle filter; observer-based control and the separation principle.
SkriptLecture notes available on course website: Link
Voraussetzungen / BesonderesRequirements: Introductory probability theory and matrix-vector algebra.
151-0623-00LETH Zurich Distinguished Seminar in Robotics, Systems and Controls Information
Findet dieses Semester nicht statt.
W1 KP1SB. Nelson, M. Chli, R. Gassert, M. Hutter, W. Karlen, R. Riener, R. Siegwart
KurzbeschreibungThis course consists of a series of seven lectures given by researchers who have distinguished themselves in the area of Robotics, Systems, and Controls.
LernzielObtain an overview of various topics in Robotics, Systems, and Controls from leaders in the field. Please see Link for a list of upcoming lectures.
InhaltThis course consists of a series of seven lectures given by researchers who have distinguished themselves in the area of Robotics, Systems, and Controls. MSc students in Robotics, Systems, and Controls are required to attend every lecture. Attendance will be monitored. If for some reason a student cannot attend one of the lectures, the student must select another ETH or University of Zurich seminar related to the field and submit a one page description of the seminar topic. Please see Link for a suggestion of other lectures.
Voraussetzungen / BesonderesStudents are required to attend all seven lectures to obtain credit. If a student must miss a lecture then attendance at a related special lecture will be accepted that is reported in a one page summary of the attended lecture. No exceptions to this rule are allowed.
151-0840-00LPrinciples of FEM-Based Optimization and Robustness Analysis Information W5 KP2V + 2UB. Berisha, P. Hora, N. Manopulo
KurzbeschreibungDie Vorlesung vermittelt Grundlagen im Bereich stochastischer Simulationen und nichtlinearer Optimierungsmethoden. Zuerst werden die Methoden der nichtlinearen Optimierung für komplexe mechanische Systeme hergleitet und anschliessend auf reale Prozesse angewendet. Typische Anwendungen von stochastischen Methoden zur Vorhersage von Prozessstabilität und Robustheitsbewertungen werden behandelt.
LernzielIm Allgemeinen sind reale Systeme nichtlinear. Desweiteren unterliegen reale Prozesse Prozessschwankungen. Trotzdem werden gewöhnlich bei der Simulation zufallsunabhängige Randbedingungen mit konstanten Parametern angenommen. Demzufolge können mit diesen Ergebnissen keine Rückschlüsse auf das reale Systemverhalten gezogen werdnen. Das Ziel dieser Vorlesung ist es, einen Einblick in die Methoden der stochastischen Simulation und der nichtlinearen Optimierung zu geben.

Die Studierenden lernen mathematische Methoden wie bspw. gradientenbasierte und gradientenfreie Methoden (Genetische Algorithmen) kennen. Er lernt den Umgang mit Optimierungsprogrammen (Matlab Optimization Toolbox) und löst damit grundlegende Probleme im Bereich Optimierung und Stochastik.

Desweiteren wird besonders auf die Optimierung und Robustheitsuntersuchungen von Ingenieursproblemen, unter Anwendung von kommerzieller Finite Elemente Software wie ABAQUS und Optimierungssoftware wie LS-Opt, eingegangen.
InhaltGrundlagen der nichtlinearen Optimierung

- Einführung in die Problematik der nichtlinearen Optimierung und der stochastischen Prozesssimulation
- Grundlagen der nichtlinearen Optimierung
- Einführung in LS-Opt
- Design of Experiments DoE
- Einführung in die nichtlineare FEM

Optimierung nichtlinearer Systeme

- Anwendungsfall: Optimierung einfacher Tragwerke (ABAQUS, LS-Opt)
- Optimierung mittels Metamodellen
- Einführung in die Strukturoptimierung
- Einführung in die Geometriparametrisierung zur Formoptimierung

Robustheit und Sensitivität mehrparametriger Systeme

- Einführung in die Stochastik und Robustheit von Prozessen
- Sensitivitätsanalysen
- Anwendungsbeispiele
Skriptja
151-0944-00LCase Studies on Earth's Natural Resources
Findet dieses Semester nicht statt.
W3 KP3SM. Mazzotti
KurzbeschreibungBy working on case studies, built around everyday consumer products, and by applying engineering principles (e.g. material and energy balances), students will gain insight into natural resources, their usage in today's society, the challenges and the opportunities ensuing from the need to make their use long-term sustainable.
LernzielThe students are supposed to gain insight about our natural resources, and how their usage and supply relate to our society and to us as individuals. The students will analyse how the natural resources form and change, how they are extracted and used, and how we can utilize them in a sustainable way.
InhaltThe students will analyze processes and products in terms of their use of natural resources. The study will use everyday consumer products as examples, will use engineering principles together with physics and chemistry fro the analysis, and will be based on documentation collected by the students withe the help of lecturer and assistants. Through these examples, the students will be made familiar with issues about the circular economy and recycling.
SkriptHandouts during the class.
LiteraturWalther, John V., "Earth's natural resources", (2014) Jones & Bartlett Learning // Oberle, B., Bringezu, S., Hatfield-Dodds, S., Hellweg, S., Schandl, H., Clement, J., "Global Resources Outlook 2019: Natural resources for the future we want - A Report of the International Resource Panel", (2019) United Nations Environment Programme.
Voraussetzungen / BesonderesStudents must be enrolled in a MSc or doctoral program at ETH Zurich.
151-1053-00LThermo- and Fluid DynamicsZ0 KP2KP. Jenny, R. S. Abhari, K. Boulouchos, G. Haller, C. Müller, N. Noiray, D. Poulikakos, H.‑M. Prasser, T. Rösgen, A. Steinfeld
KurzbeschreibungCurrent advanced research activities in the areas of thermo- and fluid dynamics are presented and discussed, mostly by external speakers.

The talks are public and open also for interested students.
LernzielKnowledge of advanced research in the areas of thermo- and fluid dynamics
InhaltCurrent advanced research activities in the areas of thermo- and fluid dynamics are presented and discussed, mostly by external speakers.
151-9902-00LWorkshop on Intellectual Property Rights Belegung eingeschränkt - Details anzeigen W1 KP1SC. Soltmann
KurzbeschreibungThe 2-day workshop is an introduction to intellectual property rights. It informs participants about the different methods of protecting technical know-how and puts them in a position to use this knowledge for their own research. The workshop includes exercises and use cases tailored to mechanical engineers. An outlook on IP strategy for start-ups rounds up the program.
LernzielKnowledge about patents and other intellectual property (IP) rights has become increasingly important for scientists in the field of mechanical engineering. In fact, many doctoral students disclose their first inventions here at ETH Zurich. The workshop is an excellent introduction to the fundamental aspects of intellectual property (IP) rights and prepares you well for your first patent application.
InhaltPresentations and exercises on intellectual property rights (what is new? what is inventive? what is the role of a patent claim?), patent search, invention disclosures at ETH Zurich, commercialization of an invention by an ETH spin-off.
SkriptPresentation slides.
Voraussetzungen / BesonderesThe course is limited to 25 participants. In case more students sign up, ETH transfer will make the selection based on pre-defined criteria (even distribution over the various research groups, 2nd year students first).
101-0178-01LUncertainty Quantification in Engineering Information W3 KP2GS. Marelli
KurzbeschreibungUncertainty quantification aims at studying the impact of aleatory and epistemic uncertainty onto computational models used in science and engineering. The course introduces the basic concepts of uncertainty quantification: probabilistic modelling of data (copula theory), uncertainty propagation techniques (Monte Carlo simulation, polynomial chaos expansions), and sensitivity analysis.
LernzielAfter this course students will be able to properly pose an uncertainty quantification problem, select the appropriate computational methods and interpret the results in meaningful statements for field scientists, engineers and decision makers. The course is suitable for any master/Ph.D. student in engineering or natural sciences, physics, mathematics, computer science with a basic knowledge in probability theory.
InhaltThe course introduces uncertainty quantification through a set of practical case studies that come from civil, mechanical, nuclear and electrical engineering, from which a general framework is introduced. The course in then divided into three blocks: probabilistic modelling (introduction to copula theory), uncertainty propagation (Monte Carlo simulation and polynomial chaos expansions) and sensitivity analysis (correlation measures, Sobol' indices). Each block contains lectures and tutorials using Matlab and the in-house software UQLab (Link).
SkriptDetailed slides are provided for each lecture. A printed script gathering all the lecture slides may be bought at the beginning of the semester.
Voraussetzungen / BesonderesA basic background in probability theory and statistics (bachelor level) is required. A summary of useful notions will be handed out at the beginning of the course.

A good knowledge of Matlab is required to participate in the tutorials and for the mini-project.
101-0190-08LUncertainty Quantification and Data Analysis in Applied Sciences Information
The course should be open to doctoral students from within ETH and UZH who work in the field of Computational Science. External graduate students and other auditors will be allowed by permission of the instructors.
W3 KP4GE. Chatzi, P. Koumoutsakos, S. Marelli, V. Ntertimanis, K. Papadimitriou
KurzbeschreibungThe course presents fundamental concepts and advanced methodologies for handling and interpreting data in relation with models. It elaborates on methods and tools for identifying, quantifying and propagating uncertainty through models of systems with applications in various fields of Engineering and Applied science.
LernzielThe course is offered as part of the Computational Science Zurich (CSZ) (Link) graduate program, a joint initiative between ETH Zürich and University of Zürich. This CSZ Block Course aims at providing a graduate level introduction into probabilistic modeling and identification of engineering systems.
Along with fundamentals of probabilistic and dynamic system analysis, advanced methods and tools will be introduced for surrogate and reduced order models, sensitivity and failure analysis, parallel processing, uncertainty quantification and propagation, system identification, nonlinear and non-stationary system analysis.
InhaltThe topics to be covered are in three broad categories, with a detailed outline available online (see Learning Materials).
Track 1: Uncertainty Quantification and Rare Event Estimation in Engineering, offered by the Chair of Risk, Safety and Uncertainty Quantification, ETH Zurich (18 hours)
Lecturers: Prof. Dr. Bruno Sudret, Dr. Stefano Marelli
Track 2: Bayesian Inference and Uncertainty Propagation, offered the by the System Dynamics Laboratory, University of Thessaly, and the Chair of Computational Science, ETH Zurich (18 hours)
Lecturers: Prof. Dr. Costas Papadimitriou, Dr. Georgios Arampatzis, Prof. Dr. Petros Koumoutsakos
Track 3: Data-driven Identification and Simulation of Dynamic Systems, offered the by the Chair of Structural Mechanics, ETH Zurich (18 hours)
Lecturers: Prof. Dr. Eleni Chatzi, Dr. Vasilis Dertimanis
The lectures will be complemented via a comprehensive series of interactive Tutorials will take place.
SkriptThe course script is composed by the lecture slides, which will be continuously updated throughout the duration of the course on the CSZ website.
LiteraturSuggested Reading:
Track 2 : E.T. Jaynes: Probability Theory: The logic of Science
Track 3: T. Söderström and P. Stoica: System Identification, Prentice Hall International, Link see Learning Materials.
Xiu, D. (2010) Numerical methods for stochastic computations - A spectral method approach, Princeton University press.
Smith, R. (2014) Uncertainty Quantification: Theory, Implementation and Applications SIAM Computational Science and Engineering,
Lemaire, M. (2009) Structural reliability, Wiley.
Saltelli, A., Ratto, M., Andres, T., Campolongo, F., Cariboni, J., Gatelli, D., Saisana, M. & Tarantola, S. (2008) Global Sensitivity Analysis - The Primer, Wiley.
Voraussetzungen / BesonderesIntroductory course on probability theory
Fair command on Matlab
227-0224-00LStochastic SystemsW4 KP2V + 1UF. Herzog
KurzbeschreibungProbability. Stochastic processes. Stochastic differential equations. Ito. Kalman filters. St Stochastic optimal control. Applications in financial engineering.
LernzielStochastic dynamic systems. Optimal control and filtering of stochastic systems. Examples in technology and finance.
Inhalt- Stochastic processes
- Stochastic calculus (Ito)
- Stochastic differential equations
- Discrete time stochastic difference equations
- Stochastic processes AR, MA, ARMA, ARMAX, GARCH
- Kalman filter
- Stochastic optimal control
- Applications in finance and engineering
SkriptH. P. Geering et al., Stochastic Systems, Measurement and Control Laboratory, 2007 and handouts
327-2140-00LMicroscopy Training FIB-SEM Belegung eingeschränkt - Details anzeigen
Number of participants limited to 6. PhD students will be asked for a fee. Link

Registration form: (Link)
W1 KP2PP. Zeng, A. G. Bittermann, S. Gerstl, L. Grafulha Morales, K. Kunze, J. Reuteler
KurzbeschreibungThe introductory course on Focused Ion Beam (FIB) provides theoretical and hands-on learning for new operators, utilizing lectures, demonstrations and hands-on sessions.
Lernziel- Set-up, align and operate a FIB-SEM successfully and safely.
- Accomplish operation tasks and optimize microscope performances.
- Perform sample preparation (TEM lamella, APT probe…) using FIB-SEM.
- Perform other FIB techniques, such as characterization
- At the end of the course, students will know how to set-up FIB-SEM, how to prepare TEM lamella/APT probe and how to utilize FIB techniques.
InhaltThis course provides FIB techniques to students with previous SEM experience.
- Overview of FIB theory, instrumentation, operation and applications.
- Introduction and discussion on FIB and instrumentation.
- Lectures on FIB theory.
- Lectures on FIB applications.
- Practicals on FIB-SEM set-up, cross-beam alignment.
- Practicals on site-specific cross-section and TEM lamellar preparation.
- Lecture and demonstration on FIB automation.
Literatur- Detailed course manual.
- Giannuzzi, Stevie: Introduction to focused ion beams instrumentation, theory, techniques, and practice, Springer, 2005.
- Orloff, Utlaut, Swanson: High resolution focused ion beams: FIB and its applications, Kluwer Academic/Plenum Publishers, 2003.
Voraussetzungen / BesonderesThe students should fulfil one or more of these prerequisites:
- Prior attendance to the ScopeM Microscopy Training SEM I: Introduction to SEM (327-2125-00L).
- Prior SEM experience.
327-2224-00LMaP Distinguished Lecture Series on Additive Manufacturing
This course is primarily designed for MSc and doctoral students. Guests are welcome.
W1 KP2SL. Schefer, M. Meboldt, A. R. Studart
KurzbeschreibungThis course is an interdisciplinary colloquium on Additive Manufacturing (AM) involving different internationally renowned speakers from academia and industry giving lectures about their cutting-edge research, which highlights the state-of-the-art and frontiers in the AM field.
LernzielParticipants become acquainted with the state-of-the-art and frontiers in Additive Manufacturing, which is a topic of global and future relevance from the field of materials and process engineering. The self-study of relevant literature and active participation in discussions following presentations by internationally renowned speaker stimulate critical thinking and allow participants to deliberately discuss challenges and opportunities with leading academics and industrial experts and to exchange ideas within an interdisciplinary community.
InhaltThis course is a colloquium involving a selected mix of internationally renowned speaker from academia and industry who present their cutting-edge research in the field of Additive Manufacturing. The self-study of relevant pre-read literature provided in advance to each lecture serves as a basis for active participation in the critical discussions following each presentation.
SkriptSelected scientific pre-read literature (max. three articles per lecture) relevant for and discussed at the end of each individual lecture is posted in advance on the course web page
Voraussetzungen / BesonderesParticipants should have a solid background in materials science and/or engineering.
363-0764-00LProject ManagementW2 KP2VC. G. C. Marxt
KurzbeschreibungThe course gives a detailed introduction into various aspects of classic and agile project management. Established concepts and methods for initiating, planning and executing projects are introduced and major challenges discussed. Additionally the course covers different agile and hybrid project management concepts.
LernzielProjects are not only the base of work in modern enterprises but also the primary type of cooperation with customers. Students of ETH will often work in or manage projects in the course of their career. Good project management knowledge is not only a guarantee for individual but also for company wide success.

The goal of this course is to give a detailed introduction into project management, more specific participants
- will understand the basics of successful classic and agile project management
- are able to apply the concepts and methods of project management in their day to day work
- are able to identify different project management practices and are able to suggest improvements
- will contribute to projects in your organization in a positive way
- will be able to plan and execute projects successfully.
InhaltThe competitiveness of companies is driven by the development of a concise strategy and its successful implementation. Especially strategy execution poses several challenges to senior management: clear communication of goals, ongoing follow up of activities, a sound monitoring and control system. All these aspect are covered by successfully implementing and applying program and project management. As an introductory course we will focus mainly on project management.
In the last decade project management has become an important discipline in management and several internationally recognized project management methods can be found: PMBOK, IPMA ICB, PRINCE 2, etc. These frameworks have proven to be very useful in day-to-day work.
Unfortunately the environment companies are working in has changed parallel to the rise of PM as a discipline. Incremental but even more important fundamental changes happen more often and much faster than a decade ago. Experience has shown that the classic PM approaches lack the inherent dynamics to cope with these challenges. So overtime new methods have surfaced, such as SCRUM. These methods are called Agile Project Management methods and follow a dynamic model of reality, called complex adaptive systems perspective.
This course will cover both classic and agile project management topics. The first part of the semester will lay the basics by discussing the classic way of planning, organizing and executing a project based on its life cycle. Topics covered include: drafting project proposals, stake holder analysis, different aspects of project planning, project organization, project risk management, project execution, project control, leadership in projects incl. conflict mitigation strategies, termination and documentation. In the second part basic conceptual topics for agile project management such as the agile manifesto, SCRUM, Lean, Kanban, XP, rapid results are covered. The course tries to tap into pre-existing knowledge of the participants using a very interactive approach including in-class discussion, short exercises and case studies.
SkriptNo
The lecture slides and other additional material (papers, book chapters, case studies, etc.) will be available for download from Moodle before each class.
363-1039-00LIntroduction to NegotiationW3 KP2GM. Ambühl
KurzbeschreibungThe course combines different lecture formats to provide students with both the theoretical background and the practical appreciation of negotiation. A core element of the course is an introduction to the concept of negotiation engineering.
LernzielStudents learn to understand and to identify different negotiation situations, analyze specific cases, and discuss respective negotiation approaches based on important negotiation methods (i.a. Game Theory, Harvard Method).
InhaltThe course combines different lecture formats to provide students with both the theoretical background and the practical appreciation of negotiation. A core element is an introduction to the concept of negotiation engineering. The course covers a brief overview of different negotiation approaches, different categories of negotiations, selected negotiation models, as well as in-depth discussions of real-world case studies on international negotiations involving Switzerland. Students learn to deconstruct specific negotiation situations, to differentiate key aspects and to develop and apply a suitable negotiation approach based on important negotiation methods.
LiteraturThe list of relevant references will be distributed in the beginning of the course.
376-1719-00LStatistics for Experimental ResearchW3 KP2VR. van de Langenberg
KurzbeschreibungStudents will learn the necessary statistical concepts and skills to independently (1) design experiments (2) analyse experimental data and (3) report analyses and results in a scientifically appropriate manner.
LernzielAfter successful completion of the course, students should be able to:
1. Determine appropriate experimental designs and choose, justify and perform the appropriate statistical analyses using R.
2. Report analyses and results in a scientifically appropriate manner, as laid out by the Publication Manual of the American Psychological Association (APA, sixth edition).
InhaltWe will cover basic statistical concepts (e.g., central tendency, variability, data distribution), the t-test (dependent and independent), ANOVA (univariate, factorial and repeated measures), correlation, multiple regression, nonparametric techniques, validity and reliability tests, effect size, data transformation, power and sample size estimation.
SkriptLecture notes will be delivered in the form of commented presentations in Microsoft Powerpoint (i.e. pptx) format. R practical session assignments will be delivered in pdf-format.
LiteraturBoth in the lectures and in the tutorials and practical sessions, we will refer students to the following publication:

Field A, Miles J, Field Z (2013) Discovering Statistics Using R. Sage Publications Ltd, London, UK
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