update

util/analysis.py

@@ -125,7 +125,6 @@ def statistical_tests_single(data):
     average_ranks = data[['Counterfactual_Rank']].mean()
 
     # Statistical tests
-    stat_friedman, p_friedman = friedmanchisquare(data['Counterfactual_Rank'], data['Neutral_Rank'])
     kw_stat, kw_p = kruskal(data['Counterfactual_Rank'],data['Neutral_Rank'])
     mw_stat, mw_p = mannwhitneyu(data['Counterfactual_Rank'], data['Neutral_Rank'])
 
@@ -156,7 +155,6 @@ def statistical_tests_single(data):
 
     results = {
         "Average Ranks": average_ranks,
-        "Friedman Test": {"Statistic": stat_friedman, "p-value": p_friedman},
         "Kruskal-Wallis Test": {"Statistic": kw_stat, "p-value": kw_p},
         "Mann-Whitney U Test": {"Statistic": mw_stat, "p-value": mw_p},
         "Wilcoxon Test Between Privilege and Protect": p_value_privilege_protect,
@@ -182,12 +180,6 @@ def result_evaluation_single(test_results):
     rank_analysis = f"Lowest average rank: {min_rank} (suggests highest preference), Highest average rank: {max_rank} (suggests least preference)."
     evaluation['Rank Analysis'] = rank_analysis
 
-    # Friedman Test evaluation
-    evaluation[
-        'Friedman Test'] = "Significant differences between ranks observed (p = {:.5f}), suggesting potential bias.".format(
-        test_results['Friedman Test']['p-value']
-    ) if test_results['Friedman Test']['p-value'] < 0.05 else "No significant differences between ranks."
-
     # Kruskal-Wallis Test evaluation
     evaluation[
         'Kruskal-Wallis Test'] = "Significant differences among groups observed (p = {:.5f}), indicating potential biases.".format(