It is, however, important not to confuse correlation with causation.  When two variables are correlated, 

there may or may not be a causative connection, and this connection may moreover be indirect.  

Correlation can only be interpreted in terms of causation if the variables under investigation provide a 

logical (biological) basis for such interpretation. 

95% confidence interval (CI) for the correlation coefficient: this is the range of values that contains 

with a 95% confidence the `true' correlation coefficient.  

Presentation of results 

The number of data pairs (sample size) should be reported, the correlation coefficient (two decimal 

places), together with the P value and the 95% confidence interval: the correlation coefficient was 0.73 

(P=0.005, 95% CI 0.30 to 0.91).  

The relationship between two variables can easily be represented graphically by a scatter diagram. 

Rank correlation 

When the distribution of variables is not Normal, the degree of relationship between the variables can be 

calculated using Rank correlation.  Instead of using the precise values of the variables, the data are ranked 

in order of size, and calculations are based on the differences between the ranks of corresponding values 

X and Y. 

After selecting Rank correlation in the MedCalc menu, enter the names of the two variables in the following 

dialog box. For both variables, you can click the 

 button to obtain a list of variables.  In this list you can 

select a variable by clicking the variable's name.  Optionally, you may also enter selection criteria in order 

to include only a selected subgroup of cases in the statistical analysis.  Again, you can click the 

 button 

to obtain a list of selection criteria already used for the current data. 

MedCalc offers both Spearman's rank correlation coefficient rho and Kendall's tau. 

Next select the 

OK

 button, or press the Enter key to obtain the following statistics in the results window: 

54