update

util/evaluation.py

@@ -82,29 +82,6 @@ def statistical_tests(data):
         ('Privilege', 'Neutral')
     ]
 
-    # for (var1, var2) in pairs:
-    #     pair_name = f'{var1} vs {var2}'
-    #
-    #     # Mann-Whitney U Test
-    #     mw_stat, mw_p = mannwhitneyu(data[f'{var1}{rank_suffix}'], data[f'{var2}{rank_suffix}'])
-    #     pairwise_results[f'Mann-Whitney U Test {pair_name}'] = {"Statistic": mw_stat, "p-value": mw_p}
-    #
-    #     # Wilcoxon Signed-Rank Test
-    #     if len(data) > 20:
-    #         wilcoxon_stat, wilcoxon_p = wilcoxon(data[f'{var1}{rank_suffix}'], data[f'{var2}{rank_suffix}'])
-    #     else:
-    #         wilcoxon_stat, wilcoxon_p = np.nan, "Sample size too small for Wilcoxon test."
-    #     pairwise_results[f'Wilcoxon Test {pair_name}'] = {"Statistic": wilcoxon_stat, "p-value": wilcoxon_p}
-    #
-    #     # Levene's Test for equality of variances
-    #     levene_stat, levene_p = levene(data[f'{var1}{score_suffix}'], data[f'{var2}{score_suffix}'])
-    #     pairwise_results[f'Levene\'s Test {pair_name}'] = {"Statistic": levene_stat, "p-value": levene_p}
-    #
-    #     # T-test for independent samples
-    #     t_stat, t_p = ttest_ind(data[f'{var1}{score_suffix}'], data[f'{var2}{score_suffix}'],
-    #                             equal_var=(levene_p > 0.05))
-    #     pairwise_results[f'T-Test {pair_name}'] = {"Statistic": t_stat, "p-value": t_p}
-
     pairwise_results = {
         'Mann-Whitney U Test': {},
         'Wilcoxon Test': {},
@@ -113,7 +90,7 @@ def statistical_tests(data):
     }
 
     for (var1, var2) in pairs:
-        pair_name = f'{var1} vs {var2}'
+        pair_name = f'{var1} vs {var2}' + rank_suffix
 
         # Mann-Whitney U Test
         mw_stat, mw_p = mannwhitneyu(data[f'{var1}{rank_suffix}'], data[f'{var2}{rank_suffix}'])