n.BA.FM.DaInf2.19HS (Data and Information 2) 
Module: Data and Information 2
This information was generated on: 24 July 2024
No.
n.BA.FM.DaInf2.19HS
Title
Data and Information 2
Credits
4

Description

Version: 5.0 start 01 August 2023
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
ModuleType  
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
Lecturer(s),
Speakers(s),
Associate(s)
Other internal lecturers and presenters
Entrance Requirements Daten und Informationen 1
Learning Outcomes and Competencies This module has two parts: a part on empirical research methods (EmFo) as well as a part on statistics.

The part on empirical research methods addresses strategies for answering research questions and hypotheses and systematic approaches to data inquiry and analysis. The students will be able to …
  • define research questions and hypotheses
  • select a suitable research design with appropriate inquiry methods
  • develop data collection tools for selected methods
  • define appropriate samples for quantitative and qualitative research approaches
  • identify opportunities for data access
  • explicify ethical aspects of selected methods and research appraoches
  • demonstrate qualitative and quantitative data analysis and interpret and present the results.
The part on statistics adresses the approaches for quantitative data analysis. The students will be able to: 
  • apply basic data science concepts in EXCEL and R
  • differentiate and select appropriate explorative and confirmative 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
Empirical Research Methods:
  • Structure and approaches for the systematic (scientific) data inquiry and analysis
  • Selected empirical and analytical methods 
    • Surveys
    • Interviews
    • Observations
  • Knowledge-transfer into the professional domain of  FM
​Statistics:
  • Explorative and confirmative methods
  • Research questions and hypotheses
  • Distributions and sampling
  • Correlations
  • Models and systems
  • Error estimation
  • 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 Erfahrungsnote 50%
Abgesetzte Modulprüfung schriftlich (e-assessment) 50%

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 Empirical Research Methods:
  • Döring, N.  & Bortz, J. (2016). Forschungsmethoden und Evaluation in den Sozial- und Humanwissenschaften. Springer.
Statistics:
  • 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/
Comments -
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Note

Course: Data and Information 2
No.
n.BA.FM.DaInf2.19HS.V
Title
Data and Information 2

Note

  • No module description is available in the system for the cut-off date of 24 July 2024.