Mann-Whitney U Test

In many cases that a t test would be used, the assumption of normality is violated and therefore we should use the Mann-Whitney U test. The Mann-Whitney U test is used to compare differences between two independent groups when the dependent variable is either ordinal or continuous, but not normally distributed. The Mann-Whitney U test is often considered the nonparametric alternative to the independent t-test although this is not always the case. 

The assumptions for using the Mann-Whitney U test are: 

• The dependent variable should be measured at the ordinal or continuous level. 

• The independent variable should consist of two categorical, independent groups. 
• You should have independence of observations, which means that there is no relationship between the observations in each group or between the groups themselves. 
• The Mann-Whitney U test can be used when your two variables are not normally distributed. 

For further reading about Mann-Whitney U test using SPSS, you may read this: 

https://statistics.laerd.com/spss-tutorials/mann-whitney-u-test-using-spss-statistics.php 

or watch these videos: 

References 

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

Rosenthal, R., Rosnow, R., 2008. Essentials of Behavioral Research: Methods and Data Analysis, third ed. McGraw Hill, Boston, MA. 

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.