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

Chi-square Test

A typical case where the assumption of normality cannot hold is when we examine questions that has “yes” and “no” for answers or any kind of dichotomous variables. The chi-square test for independence, also called Pearson’s chi-square test or the chi-square test of association, is used to discover if there is a relationship between two categorical variables. 

The assumptions for using the Chi-square test are: 

  • The two variables should be measured at an ordinal or nominal level (i.e., categorical data).  
  • The two variables should consist of two or more categorical, independent groups. 


For further reading about Chi square test using SPSS, you may read this: 

or watch these videos: 


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. 

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.

Salcedo, J., & McCormick, K. (2020). SPSS statistics for dummies. John Wiley & Sons.