Analytical Validation of NovoNumeric: An Indigenous, High-Performance Statistical Software for Indian Medical Research Authors Mohammed Jaseem Ibrahim K. NovoNumeric Software, Thiruvananthapuram, India. DOI: https://doi.org/10.64383/irjss.202501227 Keywords: Data Analysis, Health Technology, Statistical Software, Clinical Validation, Medical Research Software Abstract Statistical analysis is a fundamental pillar of medical research, yet many powerful software options come with a steep learning curve or prohibitive costs. NovoNumeric is a novel statistical software for macOS designed to address this by balancing accessibility with high performance. This study provides the first formal analytical validation of NovoNumeric by comparing its analytical output against established gold-standard packages. A comparative validation study was performed using an anonymized clinical dataset (n=174) from a prospective observational study on diabetic foot infections, conducted at Sree Uthradom Thirunal Academy of Medical Sciences, Thiruvananthapuram (Ethical Approval No. 22/IEC/SUTAMS/2023). Parallel analyses—including descriptive statistics, independent t-tests, chi-square tests, Pearson's correlation, and multiple linear regression—were conducted using NovoNumeric (v4.0), R (v4.3.1), and SPSS (v28). The primary outcome was the equivalency of numerical results. For every statistical test performed, NovoNumeric produced identical outputs to R and SPSS, with maximum absolute differences < 1 x 10-8. These findings confirm that NovoNumeric is a valid, reliable, and high-performance tool for core statistical analyses in medical research, demonstrating its suitability as a cost-effective solution for Indian academic and clinical research institutions. Author Biography Mohammed Jaseem Ibrahim K., NovoNumeric Software, Thiruvananthapuram, India. Creator: NovoNumeric Junior Resident, SUT Academy of Medical Sciences, Venkode, Thiruvananthapuram, India. References [1] R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing; 2023. Available from: https://www.R-project.org/ [2] IBM Corp. IBM SPSS Statistics for Windows, Version 28.0. IBM Corp; 2021. [3] StataCorp. Stata Statistical Software: Release 17. StataCorp LLC; 2021. [4] Apple Inc. Accelerate. Apple Developer Documentation. 2023. Available from: https://developer.apple.com/documentation/accelerate [5] Ibrahim MKJ. NovoNumeric: An Accessible, High-Performance Statistical Software for Advancing Medical Research on macOS. International Research Journal of Scientific Studies. 2025; 2(8): 1-9. https://doi.org/10.64383/irjss.20250924 [6] Posit team. RStudio: Integrated Development Environment for R. Posit; 2023. 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International Research Journal of Scientific Studies, 2(10), 1–7. https://doi.org/10.64383/irjss.202501227 More Citation Formats ACM ACS APA ABNT Chicago Harvard IEEE MLA Turabian Vancouver Download Citation Endnote/Zotero/Mendeley (RIS) BibTeX Issue Vol. 2 No. 10 (2025): December Section Research Papers Categories Artificial Intelligence Data Science License Copyright (c) 2025 International Research Journal of Scientific Studies This work is licensed under a Creative Commons Attribution 4.0 International License. International Research Journal of Scientific Studies is an open-access journal that publishes articles under a Creative Commons Attribution 4.0 International License (CC BY 4.0). This license allows for the widest possible dissemination and use of the articles, while ensuring that the authors receive proper credit for their work. Article Licensing 1. 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