Spearman correlation is a non-parametric test to determine the degree of correlation (association) between two variables.
The requirements of the test are:
Data in existing Excel worksheets can be used and should be arranged in a List dataset layout. The dataset must contain two ordinal or continuous scale variables.
When entering new data we recommend using New Dataset to create a new 2 variables dataset ready for data entry.
To start the test:
Excel 97, 2000, 2002 & 2003:
Select any cell in the range containing the dataset to analyse, then click Analyse on the Analyse-it toolbar, click Correlation then click Spearman.
The report shows the number of observations analysed, and, if applicable, how many missing cases were pairwise deleted.
The Spearman rs correlation statistic and confidence interval are shown.
METHOD The confidence interval is calculated using the Fisher's Normal transformation (see  or ).
The hypothesis test is shown. The p-value is the probability of rejecting the null hypothesis, that the variables are independent, when it is in fact true. A significant p-value implies that the two variables are correlated.
METHOD The p-value is calculated using the t- approximation (see ). For small sample sizes ≤ 30 exact tables should be used (see ), or use the Kendall correlation which calculates exact p-values for small samples.
When both variables are continuous scale the scatter plot (see below) shows a visual assessment of the strength of association.