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Spearman rank correlation coefficient in SPSS

Spearman rank correlation coefficient in SPSS

Spearman correlation coefficient is a nonparametric measure of rank correlation. It measures the strength and direction of the association between two ranked variables.

Assumptions

  1. Two variables should be continuous.

  2. Two variables should represent paired observations.

  3. There should be a monotonic relationship between two variables. A monotonic relationship exists either when variables increase in value together or when one variable value increases and another variable value decreases.

History Score and Geography Score of a student are considered as variables.

In SPSS, Spearman correlation coefficient can be found in Analyze > Correlate > Bivariate

Then, we will get ‘Bivariate Correlations’ dialog box.

Add the variables History Score and Geography Score to Variables: box. 

We have to tick the ‘Spearman’ box in ‘Correlation Coefficients’ group.

Then, click on Ok.

Output of Spearman correlation coefficient

We will get ‘Correlations’ table

The table presents the Pearson correlation coefficient, its value of significance and the sample size.

Here, consider one of the highlighted cells (two cells are same) and find that correlations in the main diagonal are equal to 1. This is because a variable is always correlated with itself perfectly.

Here, the Spearman correlation is 0.732 and it is statistically significant (p=0.000) and its sign is “+”. Therefore, the direction of the relationship is positive. 

Data: Spearman’s_Correlation_Data.sav

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