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Spearman's Rho Correlation

Introduction

A Spearman's 'rho' 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 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: Parametric or Not Guide (PDF)

If your data is parametric you should consider Pearson's 'r' Correlation

 

Test Procedure

  1. Click Analyze > Correlate > Bivariate 

  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.

  3. Select Spearman as the Correlation Coefficient 

  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.