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:
References
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.