Advanced data analysis

0HM120

About this course

Solid execution of one's professional duties as an HTI engineer requires in-depth knowledge of and experience with the statistical processing of data. Besides assisting the student in mastering several more advanced statistical techniques (path models, contrast analysis), the advanced data analysis course allows students to consolidate their bachelor level statistical knowledge by developing a critical attitude toward data analysis and gaining experience with dealing with statistical problems that are typically relevant to the HTI domain. Taken together, the course provides students with sufficient statistical and data analytical expertise to analyze and interpret not only one's own research data (e.g., research project or graduation project), but also data collected and /or analyzed by other researchers in their domain.

Throughout the course the following topics will be addressed:

  • Data analysis as a way of asking theoretically guided statistical questions
  • The ins and outs of hypothesis testing, power, replication, and meta-analysis
  • Working with SPSS and STATA
  • Path analysis using regression (e.g., mediation)
  • Analysis of covariance and its various uses
  • Contrast analysis

Learning outcomes

After successful completion of the course, the student

  • can explain the fundamentals of the theories behind the targeted statistical techniques
  • has acquired the skills necessary for applying these techniques, on his or her own, to problems relevant for the HTI, and to appropriately report on the results of statistical analyses
  • has learned to read and master primary theoretical literature in the domains of data-analysis and statistics.
  • can reflect critically on his or her own data analysis skills and activities and on that of others; being able, for example, to explain what constitutes proper data analysis (e.g., with respect to sample size, robustness, and the selection of appropriate techniques).

Prior knowledge

You must meet one of the following collections of requirements

  • Collection 1
  • Completed Final examination Bsc program
  • Collection 2
  • Completed Pre-Master

Resources

  • Selected book chapters and articles (mandatory and recommended readings)
  • Gpower http://www.gpower.hhu.de (Heinrich Heine Universität Düsseldorf)
  • SPSS 23 http://www-01.ibm.com/software/analytics/spss/ (IBM)
  • Stata http://www.dpc-software.nl/ (Stata Corp LP)

Additional information

  • Credits
    ECTS 5
  • Level
    master
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