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.