Introduction
A Spearman's 'rho' Correlation compares the relationships between two variables. Common examples include height and weight, IQ and Test Score, and Strenght and Speed.
It is considered a non-parametric test and therefore is only suitable for non-parametric data. To check if your data is parametric, please check out the dedicated guide here: Parametric or Not Guide
If your data is parametric you should consider Pearson's 'r' Correlation
Test Procedure
Step 1: Click Analyze > Correlate > Bivariate
Step 2: Within the 'Bivariate Correlations' window, select the two variables you intend to analyse and move them to the 'Variables' box using the blue arrow.
Step 3: Select Spearman as the Correlation Coefficient
Step 4: Select Continue à OK
Results
SPSS will generate one Correlations table.
Correlations
This table shows the three statistics we need to report when running a Spearman's 'rho' correlation, the Correlation Coefficient (Correlation), the significance/ p-value (Sig (2-tailed)), and the sample size (N)
Reporting the Results in APA Formatting
The relationship between the length of a porcupine and its number of spines was compared. A Spearman's 'Rho' Correlation indicated that the two measurements were significantly related, r=.69, p<.001, N=31.
