Journal of Survey Statistics and Methodology, published by Oxford University Press Inc, is a pivotal platform for advancing research in the fields of Applied Mathematics, Social Sciences, and Statistics. With its ISSN 2325-0984 and E-ISSN 2325-0992, this journal has firmly established itself since its inception in 2013, achieving a remarkable Q1 quartile ranking across various disciplines in 2023, indicating its significant impact and prestige in the academic community. It serves as a key resource for researchers and practitioners committed to enhancing survey methodology, statistical practices, and data-driven decision-making processes. The journal provides a comprehensive assembly of scholarly articles, methodological advancements, and theoretical insights, aimed at enriching the landscape of survey statistics and related domains. Scholars are encouraged to contribute and stay abreast of the latest findings that shape the future of survey research and methodology.

JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, published by Taylor & Francis Ltd, is a premier journal dedicated to advancing the fields of statistical computation, modeling, and simulation. With a notable impact factor and a ranking in the Q2 quartile across important categories such as Applied Mathematics and Statistics, this journal serves as a vital resource for researchers, practitioners, and students alike. Established in 1972, it has consistently provided cutting-edge research insights, fostering a deeper understanding of statistical methodologies and their practical applications. Although it operates under a subscription model, the journal's commitment to disseminating high-quality research is reflected in its rigorous peer-review process and a broad international readership. With its scope spanning the intersections of statistics, probability, and computational techniques, the journal is essential for anyone looking to stay at the forefront of statistical innovation and practice.

AUSRALIAN & NEW ZEALAND JOURNAL OF STATISTICS, published by Wiley, stands as a significant platform for the dissemination of statistical knowledge and applications, specifically within the realms of statistics and probability. With an impact factor reflective of its quality and standing, the journal operates in a Q3 category for both Statistics and Probability, as well as Statistics, Probability, and Uncertainty, positioning it among the important scholarly resources in its field. As a valuable resource for researchers, professionals, and students, the journal encourages the submission of innovative research articles that push the boundaries of statistical science. Offering both print and open access options, it ensures broad accessibility, promoting a culture of collaboration and knowledge sharing across the global statistical community. Covering research from 1998 to 2024, it remains dedicated to advancing understanding in statistical methodologies and their applications, cementing its role in fostering academic discourse and practical advancements in the field.

SCANDINAVIAN JOURNAL OF STATISTICS is a premier publication in the field of statistics, published by Wiley. With an impressive impact factor that reflects its influence, this journal is recognized for its rigorous peer-reviewed research articles that contribute to the advancement of statistical methods and their applications. As a leading resource, the journal spans a wide range of topics within Statistics and Probability, maintaining a strong scholarly presence with a Q1 rank in Statistics and Probability and a Q2 rank in Statistics, Probability and Uncertainty as per the 2023 category quartiles. The journal has been diligently publishing high-quality research since 1996, and now encompasses studies up to 2024, reinforcing its commitment to providing valuable insights for researchers, professionals, and students alike. While the journal does not offer open access, it remains an essential repository of knowledge in statistical sciences, fostering collaboration and innovation within the global academic community.

Computational and Mathematical Methods is a dynamic peer-reviewed journal published by Wiley-Hindawi, focusing on innovative research in the fields of computational mathematics, mechanics, and theory. Since its transition to an Open Access format in 2022, the journal has enhanced its accessibility to researchers and practitioners globally, providing a platform for the dissemination of high-quality studies that contribute to emerging developments in mathematical modeling and computational techniques. Based in the United Kingdom, this journal is committed to fostering collaboration amongst scholars, evidenced by its rankings within Scopus: Q3 in computational mathematics, computational mechanics, and computational theory and mathematics, reflecting its relevance and influence within these critical fields. With an emphasis on interdisciplinary studies, Computational and Mathematical Methods is an essential resource for researchers, professionals, and students seeking to expand their knowledge and apply cutting-edge methodologies to practical challenges.

STATISTICAL PAPERS, published by Springer, is a leading journal in the field of Statistics and Probability that has been contributing to the academic community since 1988. With an impressive track record spanning over three decades, this journal falls within the prestigious Q2 quartile in both the Statistics and Probability and Statistics, Probability and Uncertainty categories, signifying its high-quality research output. It currently ranks #92 out of 278 in the Mathematics - Statistics and Probability category and #61 out of 168 in Decision Sciences - Statistics, Probability and Uncertainty, placing it in the 67th and 63rd percentiles respectively. Although the journal is not open access, it offers a vital platform for researchers, professionals, and students seeking to disseminate their findings and stay abreast of the latest advancements in statistical methods and applications. With its commitment to the highest standards of scholarship, STATISTICAL PAPERS plays a crucial role in shaping contemporary statistical discourse and fostering innovation within the field.

TECHNOMETRICS, established in 1959 and published by Taylor & Francis Inc, serves as a premier journal in the fields of applied mathematics, modeling and simulation, and statistics and probability. With its ISSN number 0040-1706 and E-ISSN 1537-2723, the journal has successfully converged over its decades-long history and is recognized for its substantial contributions to the quantitative analysis and application of statistical methods. TECHNOMETRICS is proud to maintain a distinguished reputation, ranking in the Q1 category for 2023 across its relevant fields, and positioning itself within the top 86th percentile in Mathematics _ Statistics and Probability as per Scopus rankings. While this journal currently does not operate under an open access model, it remains a crucial resource for researchers, professionals, and graduate students seeking insights and advancements in the realm of statistical methodologies and applications. Its commitment to disseminating high-quality research ensures it stands as an invaluable platform for innovation and scholarly discourse within the statistical community, making it essential reading for anyone interested in the evolution of applied statistical techniques.

Communications in Mathematics and Statistics, published by Springer Heidelberg, is a prominent journal dedicated to advancing research in the fields of applied mathematics, computational mathematics, and statistics. With an ISSN of 2194-6701 and an E-ISSN of 2194-671X, the journal has established itself as a vital platform for interdisciplinary scholarly communication since its inception in 2013. The journal falls within the third quartile in various rankings including applied mathematics, computational mathematics, and statistics and probability, indicating its solid position in the global research landscape. With a focus on innovative methodologies and practical applications, Communications in Mathematics and Statistics aims to bridge the gap between theoretical research and practical implementation. Researchers, professionals, and students alike will find valuable insights and cutting-edge studies that contribute to the evolution of mathematical sciences. The journal is based in Germany, with a commitment to fostering international collaboration and accessibility in mathematical research.

Stats, published by MDPI, serves as an invaluable open access platform dedicated to the fields of statistics and probability. Since its inception in 2018, the journal has been committed to disseminating high-quality research and promoting innovation in statistical methodologies through a rigorous peer-review process. Operating from Basel, Switzerland, Stats offers a global reach and aims to foster collaboration among researchers, professionals, and graduate students alike. With an impact factor indicating its emerging significance, the journal resides in the Q4 quartile of the statistics and probability category for 2023 according to Scopus rankings. This positions it within the evolving landscape of statistical research, enhancing its visibility and accessibility. Researchers are encouraged to contribute to this dynamic field and benefit from the journal's dedication to open access publishing, ensuring that research findings can reach a broad audience without barriers.

JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES, published by TARU PUBLICATIONS, is a vital platform for researchers and practitioners in the field of information science and optimization techniques. With a focus on the application of mathematical and computational methods to solve complex problems in various domains, this journal aims to advance knowledge and encourage innovative thinking. The journal's ISSN is 0252-2667 and the E-ISSN is 2169-0103. Although currently not Open Access, it strives to provide high-quality research that significantly contributes to the industry. With a commitment to rigor and excellence, the JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES is essential for anyone dedicated to enhancing their understanding and application of optimization methodologies in an ever-evolving technological landscape.