RANDOM NUMBER GENERATION: A ANALYSIS OF BENFORD'S LAW IN UNDERGRADS STUDENTS AND GERIATRICS PATIENTS

Abstract

Objectives: Study the correlation between RNG by human cognition and Benford's Law in undergraduate students at a Medical School in the countryside of the state of Sao Paulo and geriatric clinic patients. Design: The study collected data from the students and patients from the Robust Elderly Clinic of a tertiary Hospital between August 2022 and July 2023. Data collection involved a questionnaire on age, gender, education, ethnicity, occupation, and a table with 5 rows and 10 columns for the insertion of 50 numbers, chosen by the participant. Results: A total of 263 forms were collected. The average age was 27.10 (IQR- 3) years, with 66.5% being female. Frequencies of the first significant digit were: 25.59% for 1; 15.35% for 2; 10.98% for 3; 8.65% for 4; 9.67% for 5; 7.02% for 6; 8.22% for 7; 6.81% for 8, and 7.70% for 9. Applying the Chi-Square test, no statistically significant difference was found (critical χ 2 15.507; obtained χ 2 5.36). Applying Pearson's Coefficient, the value of r was 0.98. Using the Euclidean distance, the P-value was 0.9284. Conclusion: A high correlation between RNG by the human mind, in students and Robust Elderly patients, and Benford's Law was detected.