{'fraction_non_alphanumeric': 0.020107238605898123, 'fraction_numerical': 0.0013404825737265416, 'mean_word_length': 5.225, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A Note on a Nonpαrαmetric Test of Independence between Two Vectors

Marketing researchers are often confronted with situations in which it is necessary to test the statistical independence between two sets of variables. For example, Kernan [4] examined the independence between an individual's personality and his choice of decision criteria. In this study, and other related research, a question of interest has been that of testing the independence between vectors Y and Z, where Y and Z contain p and q variates respectively. The test usually applied in examining the independence between two sets of variates is canonical analysis, which assumes that the (p + q) variates are distributed multivariate normal with mean and covariance matrices: