The Digital Root Fingerprint of the Quran: A Statistical Analysis of {3,6,9} Distribution Across Five Classical Arabic Texts

This paper presents a statistical analysis of digital root distribution in Quranic vocabulary. Every word in the Quran was assigned its Abjad (Jummal) value, then reduced to a single-digit root (1-9). We measured the proportion of words falling in the set {3,6,9} across five classical Arabic texts: the Quran (78,248 words), Sahih al-Bukhari (66,345 words), Sahih Muslim (45,884 words), the pre-Islamic Mu'allaqat (792 words), and Ibn Arabi's al-Futuhat al-Makkiyya (301,798 words). Monte Carlo simulation (10,000 iterations) was used to compute p-values. The Quran alone showed statistically significant bias toward {3,6,9} (38.23%, p=0.036). All other texts fell below the significance threshold. A balance analysis revealed the Quran simultaneously achieves the highest total AND the most even distribution across all three roots (balance=0.836). The bias exists exclusively in function words; content words show no significant bias (p=0.22). The frame is intentional, the content is free.