A Pearson's 'r' correlation compares the relationships between two variables. Common examples include height and weight, IQ and Test Score, and Strength and Speed.
It is considered a parametric test and therefore is only suitable for parametric data. To check if your data is parametric, please check out the dedicated guide: Parametric or Not Guide (PDF)
If your data is non-parametric you should consider Spearman's 'rho' Correlation
Click Analyze > Correlate > Bivariate
Within the 'Bivariate Correlations' window, select the two variables you intend to analyse and move them to the 'Variables' box using the blue arrow.
Select Continue à OK
SPSS will generate one Correlations table:
This table shows the three statistics we need to report when running a Pearson's 'r' correlation, the Correlation Coefficient (Pearson Correlation), the significance/ p-value (Sig (2-tailed)), and the sample size (N)
The relationship between an ostrich's heights and its speed was compared. A Pearson's 'r' Correlation indicated that the two measurements were significantly related, r=.65, p<.001, N=174.