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Teaching and resources

The findings and results of the Swiss HR Barometer are often used in university teaching and continuing education programmes. Existing teaching materials and other resources designed to communicate current developments and challenges in the Swiss workplace are available to interested parties.

Introduction to using HRB data  

Content: This course focuses on the two stages “data collection” and “interpreting survey results”. It discusses the design and content of the Swiss HR Barometer survey so that students gain an overview of possible data analyses. Other focal points include reading a data set and the different types of variable (latent vs. direct) and items (reversed scores). 

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Learning objectives: Students familiarise themselves with the Swiss HR Barometer, build an understanding of how the data has been collected and how it might be used for analyses and/or written assignments. They learn (1) about the model used in the HR Barometers, (2) the design of the survey, (3) how the data was collected, (4) where they can file a request if they want to use the data, and (5) how to read and interpret the datasets.  

Level: Bachelor’s or master's 
Language: German 
Format: As an introduction to the datasets, over 1 to 2 lessons. The materials may be integrated into a lecture or be supplied to students for self-study, e.g., as part of a written assignment. 

Materials:

  • Introductory PowerPoint presentation on how to use the data
  • Instructions for requesting and downloading the datasets 

Author: Delia Meyer

People Analytics – statistical analyses in R 

Content: This course covers the entire analytical process from raw data processing to interpreting the results. Focal points include data processing (variable coding, handling missing values, creation of scales), descriptive statistics (means, standard deviations, correlations), group comparison (t-tests, simple regression models) and correlation analyses (simple linear regressions, moderation and mediation) 

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Learning objectives: Students learn to independently analyse survey data in the field of Human Resource Management and Work Psychology. They learn to (1) process and correct survey data in a structured manner, (2) calculate descriptive statistics, calculate and interpret simple statistical models, and (3) conduct basic statistical analyses in R

Level: Master's or advanced bachelor’s
A basic understanding of descriptive statistics is helpful

Language: English

Format: Supervised 4-lesson block refresher course  
The materials may be integrated into a lecture or be supplied to students for self-study, e.g., as part of a thesis project. 

Materials: 

  •  PowerPoint presentation “Analyzing in R” 
  • Exercise datasets (original, cleaned and ReadyData as .xlsx und .csv) 
  • Accompanying documentation (codebook and cleaning protocol) 
  • Rmarkdown script to replicate the analyses 
  • Excel templates for visualisations and simple calculations 

Please note: The data and documentation are based on a subsample (N = 143) from the 2014 HR Barometer. However, some data and variables were simulated to simplify the calculations. It is a set of hypothetical if realistic data designed to showcase typical challenges in data processing. 

Author: Dr. oec Manuela Morf 

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