Correlation (Free Access)
Correlation
If data is normally distributed (Parametric) conduct Pearson’s correlation,
For not normally distributed data (Non-Parametric) conduct Spearman’s rank correlation
- For both, the following steps are to be followed:
- Analyze
- Correlate
- Bivariate/Partial/Distances
- Bivariate for continuous variables
- Partial for one continuous and another dichotomous variable
- Move the variables to the variables tab
- Select the type of correlations
- Check the output table


Output:
- Sig. indicates whether the score would be correct 95% of the time for this sample or 99%.
- If Sig. score is less than <0.05, it indicates, the scores are significant at 95% confidence interval
- If Sig. score is less than <0.01, it indicates that the data is significant at 99% confidence interval
- Once, significance is established, the Pearson/Spearman correlation score becomes important. That score indicates the strength of the relationship.
- Scores closer to +/- 1 are strong and closer to 0 are weak. The scores can only be between -1 to +1
