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Correlation analysis is an important tool for studying relationships among different variables. The correlation coefficient r(A,B) expresses the degree of linear dependence among variables A and B. The QC.Expert program computes three types of correlation coefficients: pairwise, partial and multiple correlation coefficients.

PDF Correlation - Pdf manual

Example output
Data:
Weigth Width Strength Hardness
122.4 12.10 2.45 1715
134.6 12.97 2.69 1728
127.7 12.41 2.38 1865
141.1 13.50 2.60 1830
140.1 13.43 2.46 1831
... ... ... ...

Correlation

Protocol Output:
Correlation analysis  
Task name : Pills
   
No of rows : 28
No of columns : 4
   
Pairwise correlations (Pearson)  
Column  
weight1 - thickness1 0.757458252
weight1 - strength1 0.169614309
weight1 - hardness1 0.147036074
thickness1 - strength1 0.098601682
thickness1 - hardness1 0.121716524
strength1 - hardness1 -0.717341174
   
Multiple correlations  
Column  
weight1 0.785863793
thickness1 0.758314793
strength1 0.770106008
hardness1 0.767650632
   
Partial correlations  
Column  
weight1 - thickness1 0.731468725
weight1 - strength1 0.310442616
weight1 - hardness1 0.288575726
thickness1 - strength1 -0.052821162
thickness1 - hardness1 -0.029867326
strength1 - hardness1 -0.761645673
   
Spearman correlations  
Column  
weight1 - thickness1 0.743295019
weight1 - strength1 0.162561576
weight1 - hardness1 0.152162014
thickness1 - strength1 0.077175698
thickness1 - hardness1 0.145046524
strength1 - hardness1 -0.666119321

Graphical Output (Statistically significant pair correlations are marked with red line)
Correlation

Correlation
 
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