Course Content
Orientation, introduction to the course
1. Human-Robot Interaction (HRI)
2. Research Methods in Human-Robot Interaction
3. Smart Cities & HRI
The demand for city living is already high, and it appears that this trend will continue. According to the United Nations World Cities Report, by 2050, more than 70% of the world's population will be living and working in cities — one of many reports predicting that cities will play an important role in our future (UN-Habitat, 2022). Thus, as cities are growing in size and scope, it is shaped into complex urban landscape where things, data, and people interact with each other. Everything and everyone has become so connected that Wifi too often fails to meet digital needs, online orders don't arrive fast enough, traffic jams still clog the roads and environmental pollution still weighs on cities. New technologies, technical intelligence, and robots can contribute to the direction of finding solutions to ever-increasing problems and assist the evolution of the growing urban space.
Human-Robot Interaction
About Lesson

Normality Tests

A normality test is used to determine whether sample data has been drawn from a normally distributed population (within some tolerance). Assumption of normality means that you should make sure your data roughly fits a bell curve shape before running certain statistical tests or regression, as we will see in the assumptions for the parametric tests. 

Two of the most well-known tests of normality are the Kolmogorov-Smirnov Test and the Shapiro-Wilk Test (Lazar, 2017). The Shapiro-Wilk Test is more appropriate for small sample sizes (< 50 samples) but can also handle sample sizes as large as 2000. 


For further reading about normality tests and how to use normality test using SPSS you may read this:

To understand how to conduct a Shapiro-Wilk Normality Test in SPSS, watch this video: 

To understand how to conduct a Kolmogorov-Smirnov Normality Test in SPSS, watch this video: 


Lazar, J. , Feng, J. H., Hochheiser, H.  (2017), Research methods in human-computer interaction: Morgan Kaufmann, 2017. 

Sauro, J., and Lewis, J. R., (2016).  Quantifying the user experience: Practical statistics for user research: Morgan Kaufmann. 

Salcedo, J., & McCormick, K. (2020). SPSS statistics for dummies. John Wiley & Sons.
Dix, A. (2020). Statistics for HCI: Making Sense of Quantitative Data. Morgan & Claypool Publishers.
Robertson, J., & Kaptein, M. (2016). An introduction to modern statistical methods in HCI (pp. 1-14). Springer International Publishing.
Larson-Hall, J. (2015). A guide to doing statistics in second language research using SPSS and R. Routledge.
Aldrich, J. O. (2018). Using IBM SPSS statistics: An interactive hands-on approach. Sage Publications.