Tests for association between paired samples.
Technical details
Inputs
Two numeric variables as inputs. If you use categorical or ordinal variables, they will be coerced to numeric based on their values for the purposes of running the test.
 Variable 1 sample to analyze.
 Variable 2 second sample to compare to Variable 1.
 Type of correlation used in the test. The default is the Pearson productmoment, but Kendall's tau or Spearman's rho statistic is a rankbased measure of association which is useful when the data does not necessarily come from a bivariate normal distribution.
 Alternative hypothesis use a twosided or onesided test.

Output
 Summary Shows a nicely formatted table of the test results (default).
 R The original textbased output from the cor.test function.
 Variable names display Variable Names in the output, instead of Variable Labels.
 More decimal places display numeric values with 8 decimal places.
Output
An example output is shown below:
Additional Properties
When using this feature you can obtain additional information that is stored by inspecting it using custom R code in an item below:
#change YourReferenceName to the reference name (under Properties > General) of your analysis
item = YourReferenceName
str(item)
Acknowledgements
Uses the cor.test function from the stats R package.
Method
 In Displayr: How to Conduct a Test of Correlation Between Paired Samples
 In Q: How to Conduct a Test of Correlation Between Paired Samples