https://royalliteglobal.com/jmes/issue/feed Research Journal in Mathematics, Econometrics and Statistics 2021-05-19T20:52:18+00:00 Linda Smail Lynda.smail@gmail.com Open Journal Systems <p style="text-align: justify;">Part of Royallite Global, <em>Research Journal in Mathematics, Econometrics and Statistics</em> is a multidisciplinary journal that aims at publishing original and peer-reviewed papers across the breadths of mathematics, econometrics and statistics. Emphasis is given to both theoretical and applied research papers dealing with the applications of mathematics, econometrics and statistics in solving problems in sciences, social sciences, business, finance, economics and mathematics related topics. The journal publishes research and review articles, short communications, editorials, book reviews, case reports, and research notes.</p> https://royalliteglobal.com/jmes/article/view/621 A new approach to co-ordinate distributed, worse-case scenario, linear quadratic optimization problems 2021-05-19T20:52:18+00:00 Babacar Seck bseck@uob.edu.bh Fraser J. Forbes fraser.forbes@ualberta.ca <p>A new approach for price driven coordination, large-scale, worst-case scenario linear quadratic optimization problems is presented. The approach is based on a reformulation of the dual problem associated<br>with the centralized robust optimization problem and to modify the co-ordination scheme in order to<br>incorporate determination of the worst-case scenario. The convergence of the algorithm is proven and<br>is guaranteed when the uncertainty set, the objective function and the constraints satisfy some specic<br>properties.</p> 2021-06-26T00:00:00+00:00 Copyright (c) 2021 Babacar Seck, Fraser J. Forbes https://royalliteglobal.com/jmes/article/view/499 Simple epidemic peaks of Coronavirus Disease in UAE, 2020 2021-01-10T13:06:36+00:00 Osama Rashwan oarashwan@gmail.com <p>In 1927, the Susceptible Infected and Recovered (SIR) Mathematical Modelling originally studied by Kermack and McKendrick (A contribution to the mathematical theory of epidemics’ in the Proceedings of the Royal Society London Ser. A), The paper became a classic in infectious disease epidemiology and has been cited innumerable times. Using the data offered by Ministry of Health and Prevention, the coefficient in the system of Ordinary Differential Equations that represent the United Arab Emirates’ SIR Mathematical Modelling of COVID-19, using Microsoft Excel, and MATLAB Software is used consequently to solve and graph the solution. The idea may be extended to be website calculator or a Mobile Application giving the Infection Rate Ro, the Contact Ratio q, and the Maximum percentage of population expected to be infected linked to the daily official data website.</p> 2021-06-25T00:00:00+00:00 Copyright (c) 2021 Osama Rashwan https://royalliteglobal.com/jmes/article/view/541 Influence of visuospatial models construction and usage on college students’ academic achievement in molecular and hybridization geometries in Ghana 2021-02-27T14:19:47+00:00 Lawrence Sarpong ao.gyampoh@gmail.com Alexander Obiri Gyampoh ao.gyampoh@gmail.com Benjamin Aidoo ao.gyampoh@gmail.com Peter Haruna ao.gyampoh@gmail.com Mensah Kofi ao.gyampoh@gmail.com <p>This action research study examines the visual-spatial model’s effects on science students’ performance in molecular and hybridization geometries. Although the diagnostic test revealed both groups showed similar conceptual abilities and challenges, the studies’ outcome showed that the visuospatial model’s approach to teaching the molecular and hybridization geometries enhanced the student’s conceptual understanding. The visuospatial model representations allow students to learn about the abstract subject matter of disciplines’ scientific knowledge. Therefore, the use of visuospatial models in teaching enhances students' visual imaginations and thoughts about concepts.</p> 2021-06-27T00:00:00+00:00 Copyright (c) 2021 ALEXANDER OBIRI GYAMPOH https://royalliteglobal.com/jmes/article/view/438 The benefits of teaching inverse regression alongside Least Squares Regression: Deeper comparisons for undergraduate research 2021-01-13T06:05:48+00:00 Di Gao di.gao@shsu.edu Stephen Scariano sms094@shsu.edu <p>This article is a continuation of the authors’ previously published article, later referred as “Part I”, and entitled, “The benefits of teaching inverse regression alongside Least Squares Regression: Graphical and numerical comparisons”. In Part I of this companion series, a foundational exposition comparing Inverse Regression and Least Squares Regression was undertaken using temperature data for thirty-two American cities. Deeper relationships are explored in this article (Part II of this series). The goal is to contrast the estimates provided by both regression methods using a collection of corollaries that are accessible to undergraduate mathematics and science students who have studied Least Squares Regression. Collectively, these two articles demonstrate how to purposely enhance a general discussion of Least Squares Regression.</p> 2021-02-11T00:00:00+00:00 Copyright (c) 2021 Research Journal in Mathematics, Econometrics and Statistics