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All Journal Mikailalsys Journal of Mathematics and Statistics
M. Y. Adamu
Mathematical Sciences Programme, Abubakar Tafawa Balewa University
Engineering Mathematics Mechanical Engineering

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Multivariate Approaches to Neonatal Assessment of Newborn Babies Garba, B. A.; Baba, A. M.; Adamu, M. Y.
Mikailalsys Journal of Mathematics and Statistics Vol 3 No 3 (2025): Mikailalsys Journal of Mathematics and Statistics
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mjms.v3i3.7453

Abstract

This study examines gender-based differences in neonatal physical characteristics using multivariate statistical techniques. A total of 1,000 newborns (male and female) were sampled from the Federal University Wukari Teaching Hospital, Taraba State, Nigeria. Key anthropometric variables measured included occipito-frontal circumference (OFC), cranial circumference (CC), length of birth (LOB), abdominal circumference (AC), and weight (WT). Due to perfect correlation with other variables, AC was excluded from the multivariate analysis. The objective was to determine whether statistically significant physical differences exist between male and female neonates at birth. The study employed Hotelling’s T² test and profile analysis; however, the assumptions of homogeneity of covariance matrices (tested via Box’s M) and independence (assessed via scatter plots) were violated. To address these issues, a robust non-parametric permutation-based Hotelling’s T² test was conducted, yielding a statistically significant result (p < 0.001), indicating notable gender-based differences in multivariate mean vectors. While the main effect of Feature was highly significant (p < 0.001), revealing differences among OFC, CC, LOB, and WT, the Gender × Feature interaction was non-significant (p > 0.05), suggesting parallel measurement patterns across genders. The study concludes that gender significantly influences neonatal physical traits and that advanced multivariate methods, including Hotelling’s T² and profile analysis, are effective for analyzing high-dimensional neonatal data—even under violations of classical assumptions such as normality and homoscedasticity.
On the Numerical Solutions of Linear and Nonlinear Differential Equations by the Modified Laplace–Adomian Polynomials Method Okai, J. O.; Martha, Iliya; Adamu, M. Y.; Mujahid, U. A.; Sanda, L. N.
Mikailalsys Journal of Mathematics and Statistics Vol 4 No 1 (2026): Mikailalsys Journal of Mathematics and Statistics
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mjms.v4i1.7493

Abstract

This study employs the Laplace–Adomian Polynomial Method (LAPM) to obtain approximate solutions for both linear and nonlinear ordinary differential equations. LAPM integrates the Laplace transform with Adomian polynomials to manage nonlinear terms effectively, avoiding the need for linearization or perturbation techniques. To evaluate the method’s accuracy and computational efficiency, three representative examples were solved, with the results benchmarked against corresponding exact solutions. The numerical outcomes, presented through tables and graphical comparisons, demonstrate that LAPM provides highly accurate approximations with minimal error using only a few series terms. The findings affirm that the method is not only straightforward and computationally efficient but also broadly applicable to various nonlinear problems. Given its robustness and simplicity, LAPM holds promise for extension to more complex systems, including partial differential equations and multi-dimensional models in applied sciences.
Co-Authors Baba, A. M. Garba, B. A. Martha, Iliya Mujahid, U. A. Okai, J. O. Sanda, L. N.