MAKE MOST OF THE KNOWLEDGE NETWORK, JOIN ACADEMIC RESEARCH FOUNDATION

Journal of Statistics, Optimization and Data Science (JSODS) is a journal of innovative research thoughts. Intellectual’s thinking and researcher’s thought Processing in both the Classical & Applied areas of Mathematics, Statistics, Stochastic Processes, Optimization Modeling, Operational Research and Computational Methodologies is the scope of the journal. It’s a peer reviewed and open access journal that can facilitate the healthy and competitive knowledge discovery and its dissemination. The core objective of this endeavor is to create a knowledge sharing global platform for generating the intellectual properties. Idea conceiving, Knowledge incubation and thought processing towards the generation of brain products are the other prominent aims through this research journal. .   

JSODS invites diversified noble thoughts from all the directions of intellectuals as submission of manuscripts in the field of pure, theoretical and applied Mathematics, Statistics, Operations Research and Data Sciences. The research areas should include but not be limited to the following topics:

Mathematics: numerical analysis and approximations, algebra, geometry and topology, discrete mathematics, mathematical logic and foundations, dynamical systems, mathematical physics, mathematical finance, number theory, Combinatorics, mathematical analysis and applications, mathematical education.

Statistics: Probability theory, stochastic processes, statistical modelling, applied statistics, applied econometrics, statistical mechanics, statistical education, Bayesian statistics, biostatistics, business statistics, causal inference, computational statistics, design of experiments, engineering statistics, estimation theory, graphical modelling, high dimensional data analysis, multivariate analysis, non-parametric statistics, parametric statistics, regression analysis, reliability, sampling theory, social statistics, statistical computing, statistical inference, survival analysis, time series analysis.

Operations Research: heuristics mathematical programming, optimal control, optimization, decision sciences, expert systems, networks, queuing theory, simulation, inventory analysis, logistics, transportation, warehousing and maintenance, planning and scheduling, product and service design, project management, quality management, revenue management, supply chain management, education operations research.

Data Sciences: Data Analytics, Data Intelligence, Machine Learning, Artificial Intelligence, Statistical Data Mining, Data Warehousing, Data Processing, Data Administration, Database management, SQL, Data Modeling, Data Visualization, Predictive Analytics, Business Intelligence, Deep Learning, 

Authors should submit research papers to ARF- JSODS that are original, unpublished and not under review for publication elsewhere during the time it is being considered by JSODS. Resubmission elsewhere can only be done after JSOM has rejected the paper or the paper has been withdrawn upon the author’s request. 

1. Papers should be in MS-Word or LaTeX format with PDF, 12 point Times New Roman, A4 layout, single column, 1.5 line spacing and not exceeding 25 pages.
2. All names should be removed from the submitted paper.
3. A cover letter which includes the paper title, name(s) and institutional affiliation(s) of the author(s) should be submitted along with the manuscript,
4. An abstract of between 200-300 words should appear on the first page of the manuscript, followed by a maximum of 5 keywords.
5. All sections and subsections should be numbered in Arabic numerals.
6. Figures and Tables should be numbered consecutively.
7. Equations which are cited in the main text should be numbered consecutively on the right margin, using Arabic numerals in parenthesis.
8. References should appear in the text as Alexe (2020) or Time et al. (2020)

References should be listed alphabetically at the end of the paper as follows:

• Elton, E. J. and Gruber, M. J. (1987), Modern Portfolio Theory and Investment Analysis (3nd edition), John Wiley, New York.
• Hammer, P.L., Kogan, A. and Lejeune, M.A. (2011), “Reverse engineering country risk ratings: a combinatorial non-recursive model”, Annals of Operational Research 188, 185–213.

Authors should submit their papers to e-mail: traopadipu@gmail.com or editorjsods@gmail.com

Editor-in-Chief: Prof. Tirupathi Rao Padi (PhD), Dept. of Statistics, Ramanujan School of Mathematical Sciences,
Pondicherry University (A Central University), Puducherry, 605014, India. e-mail: traopadipu@gmail.com or editorjsods@gmail.com