docstr: Wilcoxon
  
  The Wilcoxon signed-rank test tests the null hypothesis that two related paired samples come from 
  the same distribution. In particular, it tests whether the distribution of the differences x - y 
  is symmetric about zero. It is a non-parametric version of the paired T-test.
docstr_tok: ["Wilcoxon","The","Wilcoxon","signed-rank","test","tests","the","null","hypothesis","that","two","related","paired","samples","come","from","the","same","distribution",".","In","particular",",","it","tests","whether","the","distribution","of","the","differences","x","-","y","is","symmetric","about","zero",".","It","is","a","non-parametric","version","of","the","paired","T-test","."]
code: def wilcoxon(self):
      """
      Wilcoxon
  
      The Wilcoxon signed-rank test tests the null hypothesis that two related paired samples come from
      the same distribution. In particular, it tests whether the distribution of the differences x - y
      is symmetric about zero. It is a non-parametric version of the paired T-test.
      """
  
      t, p = ranksums(self.sample1, self.sample2)
      print("=== Wilcoxon Analysis ===")
      print("The calculated t-statistic: " + str(t))
      print("The two-tailed p-value: " + str(p) + "\n")
  
file_path: CaseRecommender/caserec/evaluation/statistical_analysis.py
imports: from scipy.stats import ttest_ind, ranksums
  import numpy
label_desc: Use image node_id 4 for calling the StatisticalAnalysis obj's underlying member method code with example usage: obj.wilcoxon() without return types