Spearman’s Rank Correlation test

  • Assumptions to check:

    • Data has to be at least ordinal scale 

    • Variables represent paired observations

    • There is a monotonic relationship between the two variables with no significant outliers

  • Report design (in Methods section)

    • Report on analysis performed

    • Name the statistical package or program used in the analysis.

  • Report statistics: 

    • correlation coefficient r, p-value, t-statistic, degrees of freedom 

    • Report on assumptions

  • Example: 

    • Methods section: To check dependence of height and weight factors the non-parametric Spearman’s Rank correlation analysis was performed (in Jamovi software RRID:SCR_016142). 

    • Results section: The non- parametric Spearman’s Rank correlation analysis was used, and it showed a high and significant positive correlation between height and weight (rho = .63, p < .001, t=2.58,  df=88). The scatterplot, with a monotonic trend line, showed no violation of the monotonic relationship assumption and no significant outliers.