C15 Business Statistics I
C15 Business Statistics I
Module Coordinator/Lecturers
Study Programmes
Master's degree programme in Information Systems
Project Description
Short description
This course covers some statistical methods that can help to take decisions in business using data. These basic concepts of the statistical testing and estimating theory should – to a large extent - be known from an introductory course on probability theory and statistics in any bachelor program.
Topics
Learning objectives
Methods
Entry requirements
We require basic knowledge of probability theory and statistics, which is usually presented in a basic course on these topics in any bachelor program. The module ''Statistik'' in the bachelor program at University of Liechtenstein serves as a guideline or benchmark for this previous knowledge.
This module is prerequisite for taking the Master’s thesis Module and writing the Master’s thesis
Compulsory reading
Further reading
This course covers some statistical methods that can help to take decisions in business using data. These basic concepts of the statistical testing and estimating theory should – to a large extent - be known from an introductory course on probability theory and statistics in any bachelor program.
Topics
- Graphical and numerical characterizations of random variables and their distributions
- Framework and basic applications of testing hypotheses and estimating parameters
- Ordinary least squares method and its properties
- Simple linear regression including parameter estimation, diagnostic plots, hypothesis testing, predictions and model specifications using log-transformations
- Introduction to the software package R
Learning objectives
- Students present the distributions of random variables graphically, calculate and interpret their moments.
- Students can explain the framework of testing hypotheses and estimating parameters and apply basic procedures.
- Students criticize the assumptions of basic testing and estimating procedures and generalize the conclusions correctly.
- Students derive the minimal sample size for basic testing and estimating procedures.
- Students apply the ordinary least squares method to derive estimators and compare the statistical properties of different estimators.
- Students explain the classical linear model assumptions, run simple linear regressions, check the diagnostics plots, use log-transformations to specify models and interpret the results correctly.
Methods
- The e-learning platform Moodle will be used throughout the course for the dissemination of course material and discussions.
- Students are usually asked to read corresponding parts of the lecture notes or of the textbook in order to prepare for the upcoming lectures in advance.
- In the interactive lectures, statistical concepts will be introduced and motivated by discussing examples in detail. Assignments are offered to train these skills.
- During office hours, individual problems may be discussed with the lecturer.
- In order to analyse realistic data, the software package R will be used.
Entry requirements
We require basic knowledge of probability theory and statistics, which is usually presented in a basic course on these topics in any bachelor program. The module ''Statistik'' in the bachelor program at University of Liechtenstein serves as a guideline or benchmark for this previous knowledge.
This module is prerequisite for taking the Master’s thesis Module and writing the Master’s thesis
Compulsory reading
- Wooldridge, J.M. (2013). Introductory Econometrics. (International Student Edition, 5th edition). Mason: South Western Cengage Learning.
Further reading
- Sweeney, D.J., Williams, T.A., David R. Anderson, D.R. (2009). Fundamentals of Business Statistics (International Student Edition, 5th edition). Manson: South-Western Cengange Learning.
- Berensen, M.L., Levine, D.M., Krehbiel, T.C. (2012). Basic Business Statistics (Global Edition, 12th edition), Essex: Pearson Education Limited.
C15 Research Methods
C15 Research Methods
Module Coordinator/Lecturers
Study Programmes
Master's degree programme in Information Systems
Project Description
Short description
The module provides an introduction to research methods.
Topics
Learning objectives
Methods
This module is prerequisite for taking the Master’s thesis Module and writing the Master’s thesis
Compulsory reading
Further reading
The module provides an introduction to research methods.
Topics
- Introduction to scientific research
- Literature reviews
- Qualitative research
- Quantitative research
- Design science research
- Theories used in IS research
Learning objectives
- Students will know and understand the historical development of scientific research.
- Students will know and understand the concept of scientific research.
- Students will identify appropriate theories to explain empirical phenomena.
- Students will identify suitable research methods in order to seek answers to specific research questions.
- Students will use appropriate qualitative, quantitative, and design-oriented approaches to scientific research.
Methods
- The module integrates theoretical knowledge and practical skills in an interactive lecture.
- The e-learning platform Moodle will be used throughout the course for the dissemination of course material and discussions.
This module is prerequisite for taking the Master’s thesis Module and writing the Master’s thesis
Compulsory reading
- Kumar, R. (2014). Research methodology: A step-by-step guide for beginners. London, UK: Sage Publications.
- Recker, J. (2012). Scientific Research in Information Systems: A Beginner’s Guide. Springer, Heidelberg, Germany.
Further reading
- Bryman, A. & Bell, E. (2011) Business research methods. Oxford, UK: Oxford University Press.
- Creswell, J. W. (2003). Research design: Qualitative, quantitative, and mixed methods approaches. London, UK: Sage Publications.
- Miles, M. B. & Huberman, A. M. (1994). Qualitative data analysis. An expanded sourcebook. London, UK: Sage Publications.
- Oates, B. J. (2006). Researching information systems and computing. London, UK: Sage Publications.
- Provost, F. & Fawcett, T. (2013). Data Science for Business. Sebastopol: O'Reilly Media
Digital Form Finding
Digital Form Finding
Study Programmes
Bachelor's degree programme in Architecture
Project Description
Im Zentrum des Moduls Digitale Formfindung steht die Auseinandersetzung mit digitalen Werkzeugen zur Unterstützung des Entwurfs- und Planungsprozesses. Es werden grundlegendes theoretisches Basiswissen und Kenntnisse für den computerunterstützten Entwurfs- und Planungsprozess vermittelt, sowie in architektonischen Aufgabenstellungen praktisch vertieft.
Teaching Method
Fachstudio mit Blockunterricht (Vorlesung und Übung)
In Form von Vortrag, Projektarbeiten, Übungen, Recherche,
Visualisierung, Peerfeedback, Zeichnungen und Plänen,
sowie analogen und digitalen Modellen
In Form von Vortrag, Projektarbeiten, Übungen, Recherche,
Visualisierung, Peerfeedback, Zeichnungen und Plänen,
sowie analogen und digitalen Modellen
Learning Results
Die Studierenden …
Fachkompetenz
Methodenkompetenz
Sozialkompetenz
Selbstkompetenz
Fachkompetenz
- erkennen die grundlegenden Geometrien eines Projektes/Entwurfes und klassifizieren diese für die digitale Formfindung.
- benutzen verschiedene digitale Softwareschnittstellen (Datenaustausch mit div. Softwareprogrammen)
- erstellen einfache digitale Visualisierungen.
Methodenkompetenz
- wenden die vermittelten digitalen Formfindungsmethoden in den Übungen, Projektarbeit und eigenen Entwürfen an.
- dokumentieren und illustrieren digitale 3D-Objekte in 2D-Plänen und -Zeichnungen.
Sozialkompetenz
- beurteilen sich und die Kommilitonen in Bezug auf digitale Formfindung.
- unterstützen einander im Selbststudium und entwickeln gemeinsam Lösungsstrategien.
Selbstkompetenz
- gestalten Lernprozesse und Lernsituationen eigenständig und effizient.
Assessment Methods
Fachprojekt, Übungen, Peerfeedback und der Mitarbeit im UnterrichtAnwesenheitspflicht: min. 80% verpflichtend
C15 Start-Up-Lab - Part I
C15 Start-Up-Lab - Part I
Module Coordinator/Lecturers
Study Programmes
Master's degree programme in Entrepreneurship
C15 Start-Up Management
C15 Start-Up Management
Module Coordinator/Lecturers
Study Programmes
Master's degree programme in Entrepreneurship
C15 Innovation and Technology
C15 Innovation and Technology
Module Coordinator/Lecturers
Study Programmes
Master's degree programme in Entrepreneurship
C15 Financial and Risk Management
C15 Financial and Risk Management
Module Coordinator/Lecturers
Study Programmes
Master's degree programme in Entrepreneurship
C15 Process & Data Management
C15 Process & Data Management
Module Coordinator/Lecturers
Study Programmes
Master's degree programme in Information Systems
Project Description
Short description
The course focuses on data management and process management, which are complementary approaches for developing and implementing information systems in organizations.
Topics
Learning objectives
Methods
Compulsory reading
The course focuses on data management and process management, which are complementary approaches for developing and implementing information systems in organizations.
Topics
- Introduction to process and data management
- Information management, data management, and IS strategy
- Process modeling
- Data modeling
- Reference models
Learning objectives
- Students will know how information systems can be described from different, complementary perspectives.
- Students will know basic methods of data and process modeling in order to analyze, design, and implement information systems in organizations.
- In exercises, students will use methods of data and process modeling in order to analyze, design, and implement information systems in organizations.
Methods
- The module integrates theoretical knowledge and practical skills in an interactive lecture.
- The e-learning platform Moodle will be used throughout the course for the dissemination of course material and discussions.
Compulsory reading
- Becker, J., Kugeler, M., & Rosemann, M. (Eds.). (2003). Process Management: a guide for the design of business processes: with 83 figures and 34 tables. Springer.
- Dumas, M., La Rosa, M., Mendling, J., & Reijers, H. A. (2013). Fundamentals of business process management (pp. I-XXVII). Heidelberg: Springer.
- Watson, R. T. (2008). Data management, databases and organizations. John Wiley & Sons.
Activation in English II
Activation in English II
Module Coordinator/Lecturers
Study Programmes
Sprachkurse und Extracurriculare Veranstaltungen
Teaching Method
Interaction, coaching
Learning Results
Develop skills and competences to reach an advanced B2 level (cf. CEFR descriptors, Council of Europe)
Reading:
Speaking:
Writing:
Accuracy:
Reading:
- follow complex argumentation in specialised texts
Speaking:
- interact fluently and spontaneously with other speakers
- take an active part in discussion, expressing views precisely.
- present clear, detailed descriptions on a wide range of subjects
Writing:
- write texts showing a clear line of argumentation
Accuracy:
- possess high degree of grammatical control
Activation in English I
Activation in English I
Module Coordinator/Lecturers
Study Programmes
Sprachkurse und Extracurriculare Veranstaltungen
Teaching Method
Interaction, coaching
Learning Results
Develop skills and competences to reach the B2 threshold level (cf. CEFR descriptors, Council of Europe)
Reading:
Speaking:
Writing:
Accuracy:
Reading:
- follow argumentation in texts
- understand texts concerned with contemporary problems
Speaking:
- interact fluently with other speakers
- express different views in discussions.
- present clear descriptions on a wide range of subjects.
Writing:
- write texts showing a clear line of argumentation
Accuracy:
- possess high degree of grammatical control