In statistics, the term correlation refers to the strength and direction of a relationship between two variables.
One special type of correlation is called Spearman Rank Correlation, which is used to measure the correlation between two ranked variables. (e.g. rank of a student’s math exam score vs. rank of their science exam score in a class).
The easiest way to calculate the Spearman Rank Correlation between two variables in SPSS is by using Analyze > Correlate > Bivariate.
The following example shows how to do so in practice.
Example: How to Perform a Correlation Test in SPSS
Suppose we have the following dataset in SPSS that contains information about the math exam score and science exam score received by 10 students in a particular class:
Suppose that we would like to calculate the correlation between these two variables and perform a correlation test to determine if the correlation coefficient is statistically significant.
To do so, click the Analyze tab, then click Correlate, then click Bivariate:
In the new window that appears, drag both the Math and Science variables into the Variables box.
Then check the box next to Spearman under Correlation Coefficients.
Then check the box next to Show only the lower triangle.
Then uncheck the box next to Show diagonal:
Then click OK.
The following output will appear:
From the output we can see:
- Spearman correlation coefficient: -.481
- p-value: .229
- N (number of pairs): 10
Since the correlation coefficient is negative, it indicates that there is a negative association between Math and Science exam scores.
However, the p-value (.229) associated with this correlation coefficient is not less than .05, so the correlation is not statistically significant.
The following tutorials explain how to perform other common operations in SPSS: