{'fraction_non_alphanumeric': 0.02095238095238095, 'fraction_numerical': 0.0, 'mean_word_length': 4.9772727272727275, '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}}
Comparing the Means of Two Log-Normal Distributions: A Likelihood Approach

The log-normal distribution is one of the most common distributions used for modeling skewed and positive data. In recent years, various methods for comparing the means of two independent log-normal distributions have been developed. In this paper a higher-order likelihood based method is proposed. The method is applied to two real-life examples and simulation studies are used compare the accuracy of the proposed method to some existing methods.