anchor.diff:  The Friedman-Test is a nonparametric method to detect differences in more than two related samples.
   It's used for dependent samples, e.g. with measurements of different treatments or at different timepoints. 
   The test can be performed even on small sample sizes.
  -One benefit of this coded test is that a correction factor is applied if there are any ties in the measurements. 
  -
  -Requirements :
  +One benefit of the implemented version in FSharp.Stats is that a correction factor is applied if there are any ties in the measurements. 
  +
  +Requirements:
   
      -   sample sizes *must* be identical
      -   repeated measurements 
  -   -   no need for normal distribution
  +   -   no need for normal distribution of the samples
      -   samples must be at least ordinal scaled
   
   The idea of the test is to rank each value in every ID (as seen below).
   The test statistic approximately follows a chi-squared distribution (dof = k-1). 
   The recommended Post-Hoc-Test is Wilcoxon-signed-rank-test or a Bonferroni-correction. 
   Example taken from Universitaet Zuerich - Methodenberatung Friedman-Test ( https://www.methodenberatung.uzh.ch/de/datenanalyse_spss/unterschiede/zentral/friedman.html ) with a modification for 3 ties in one ID. 
  -References : 
  +
  +References: 
  +
     - Viv Bewick, Liz Cheek & Jonathan Ball, Statistics review 10: Further nonparametric methods (2004)
  +  
     - Salvador García,  Alberto Fernández, Julián Luengo, Francisco Herrera, Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of power (2010)
   
   
   *)
  +
   ID   |  pre   | month 1| month 2| month 3| month 4
   1       275     273      288      273      273            
   2       292     283      284      285      329     
  
positive.code: let J = [|284.;297.;284.;292.;284.|]
  
  // add everything in one sequence
  let samples =  seq{A;B;C;D;E;F;G;H;I;J}
  
  // create the test 
  createFriedmanTest samples 
  
  // results 
  (*** include-value:createFriedmanTest ***)
  
  
  
  
negative.code:     |]
  
  let dunnettResult = 
      PostHoc.dunnetts dunnetContrastMatrix dunnetExample Tables.dunnettsTwoSided095
  
  (*** include-value:dunnettResult ***)
  
  