n.BA.FM.DaInf2.19HS (Data and Information 2) 
Module: Data and Information 2
This information was generated on: 22 September 2023
Data and Information 2


Version: 4.0 start 01 August 2022
Study Programme Facility Management
Regulations Applicable RPO, 29 January 2008, School of Life Sciences and Facility Management Academic Regulations, 15 Dec. 2009, Annex for the Bachelor of Facility Management degree programme
X Compulsory Module
  Elective Module
  Optional Module
Planned Semester 2nd Semester
Module Coordinator Marcel Janser
Telephone / E-Mail +41 (0)58 934 55 07 / marcel.janser@zhaw.ch
Other internal lecturers and presenters
Entrance Requirements Daten und Informationen 1
Learning Outcomes and Competencies This module has two parts: a empiric-methodical part as well as a theoretic-statiscial part

The empric methodical part addresses strategies for answering research questions and hypotheses in student inquiry projects. It addresses the systematic approaches to professional data inquiry and analysis. The students will be able to …
  • select a suitable research design with appropriate inquiry methods
  • develop data collection tools for selected methods
  • define sampling for quantitative and qualitative research approaches
  • identify the opportunities for data access
  • explicify ethical aspects of selected methods and research appraoches
  • demonstrate qualitative and quantitative data analysis and interpret the results.
The theoretic-statistical part considers the approaches of formal data analysis. The students will be able to: 
  • apply basic data science concepts in EXCEL and R
  • differentiate and select appropriate explorative and konfirmative approaches for a given research problem
  • formulate research questions and hypotheses and validate their internal consistency
  • identify and verify correlations through empirical tests 
  • define and validate simple empirical models and systems
  • estimate measurement errors and the data quality
  • make evidence-based statements and take decisions
Module Content
  • Structure and approaches for the systematic (scientific) data inquiry and analysis
  • Selected empirical and analytical methods 
    • quantitative Interviews
    • qualitative Surveys
    • Observations
    • sensor-based automatic Monitoring
  • Knowledge-transfer into the professional domain of  FM
  • Explorative and confirmative methods
  • Research questions and hypotheses
  • Distributions and sampling
  • correlations
  • Models and systems
  • Errorestimation
  • Evidence-based statements and decision making
Follow-up Modules Projektarbeit und Projektmanagement
Methods of Instruction
  • Lectures with assignments 
  • Digital Workshop: Tool usage
  • Case-based inquiry methods
  • Discussions and brainstormings
  • Exercises for methods and tools
  • Activities in the Moodle virtual classroom
Digital Resources
Moodle course
Classroom Attendance Requirement no
Assessment Written Exam at the end of the semester (e-assessment): 20%
Graded written exercises (electronic): 80%

If there is a low number of participants, the lecturer may change the form of a repeat examination after consultation with the head of the study programme: e.g. an oral examination can be used to replace a written one. Please report any changes to the form of examinations by e-mail to pruefungsadmin.lsfm@zhaw.ch and Cc. Head of study programme.
Language of Instruction German
Compulsory Reading -
Recommended Reading
  • Sauer, S. (2019). Moderne Datenanalyse mit R. Daten einlesen, aufbereiten, visualisieren, modellieren und kommunizieren. Springer Gabler. 
  • Wickham, H. (2021). ggplot2, Use R! Cham, CH: Springer Nature. https://ggplot2-book.org/
  • Döring, N.  & Bortz, J. (2016). Forschungsmethoden und Evaluation in den Sozial- und Humanwissenschaften. Springer.
Comments -


Course: Data and Information 2
Data and Information 2


  • No module description is available in the system for the cut-off date of 22 September 2023.