JIRSS - Journal of the Iranian Statistical Society is a prominent academic journal dedicated to the field of statistics and probability, published by the esteemed Iranian Statistical Society. With its ISSN number 1726-4057 and E-ISSN 2538-189X, this journal serves as a vital platform for disseminating cutting-edge research and advancements in statistical methodology and its applications. Established in 2011, JIRSS has consistently contributed to the academic community, achieving a 2023 Scopus rank of #180 out of 278 in its category, placing it within the 35th percentile in the dynamic domain of Mathematics: Statistics and Probability. As an Open Access publication, it enhances accessibility for researchers, professionals, and students, facilitating a wider engagement with innovative statistical techniques and theories. The journal aims to foster collaboration and knowledge exchange among statisticians, ultimately enriching the field and its impact on various scientific disciplines.

Journal of Multivariate Analysis, published by Elsevier Inc, stands as a pivotal resource in the disciplines of Numerical Analysis and Statistics. With a history of scholarly contribution since 1971, this journal has maintained a reputation for excellence, evidenced by its Q2 ranking in critical categories as of 2023. The journal covers a wide array of topics within multivariate statistical methods and their applications, making it an essential publication for researchers, professionals, and students seeking to deepen their understanding and application of sophisticated analytical techniques. Although not open-access, the journal provides valuable insights into the ever-evolving fields of statistics and probability, enabling readers to access and contribute to cutting-edge research up to the year 2024. By addressing significant theoretical and practical challenges in statistical analysis, Journal of Multivariate Analysis fosters a community of intellectual rigor and innovation.

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.

Canadian Journal of Statistics - Revue Canadienne de Statistique is a prestigious publication in the field of statistics, managed by Wiley. Since its inception in 1973, this journal has served as an essential resource for researchers, practitioners, and students, offering insights into a diverse range of statistical methodologies and applications. With its impact reflected in its 2023 categorization as Q2 in Statistics and Probability and Q3 in Statistics, Probability and Uncertainty, the journal stands out among its peers, exemplifying rigorous standards in empirical research. The journal's ISSN is 0319-5724 and its E-ISSN is 1708-945X, providing a robust platform for the dissemination of knowledge in the field. While it does not offer open access, the journal remains highly regarded and well-cited, contributing significantly to the advancement of statistical theory and practice. As it continues to publish cutting-edge research through to 2024, the Canadian Journal of Statistics is a must-read for anyone seeking to stay informed on the latest trends and developments in statistics.

Austrian Journal of Statistics, published by the AUSTRIAN STATISTICAL SOC, serves as a prominent platform for disseminating innovative research in the fields of statistics and applied mathematics. Established as an open-access journal in 1996, it aims to promote the exchange of knowledge and advancements among researchers, academics, and practitioners, particularly in Austria and beyond. With an ISSN of 1026-597X, this journal has gained recognition despite its current standing in the lower quartiles in various Scopus rankings. It covers a wide breadth of topics including statistics, probability, and uncertainty, appealing to a diverse audience of researchers aiming to enhance their understanding of these critical disciplines. By offering unrestricted access to its content, the Austrian Journal of Statistics provides invaluable resources for both emerging and established voices in the field, making it a vital source for academics and professionals alike. Research published here contributes to the ongoing dialogue surrounding statistical methodologies and applications, making it indispensable for anyone engaged in data analysis and interpretation.

STATISTICA NEERLANDICA is a prestigious peer-reviewed journal published by Wiley, focusing on the fields of statistics and probability. Established in 1946 and addressing key issues in statistical theory and its applications, the journal has significantly contributed to the development of modern statistical practices. With an impressive Q2 categorization in both Statistics and Probability, as well as Statistics, Probability, and Uncertainty, STATISTICA NEERLANDICA stands out within its field, ranking in the 62nd percentile among its peers in mathematics, specifically in statistics and probability. Researchers, professionals, and students can benefit from its rigorous scholarship and innovative methodologies, aiding in the advancement of statistical science. Although the journal does not operate under an open access model, it maintains a commitment to disseminating high-quality research, making it a vital resource for those engaged in statistical inquiry.

The Chilean Journal of Statistics is a vital resource for researchers, professionals, and students dedicated to the field of statistics and probability. Published by SOC CHILENA ESTADISTICA-SOCHE, this journal serves as a platform for the dissemination of innovative research and advancements in statistical methodologies, data analysis, and applications. With an ISSN of 0718-7912 and E-ISSN 0718-7920, the journal features contributions from the statistical community in Chile and beyond, reflecting its growing influence as evidenced by its classification in the Q3 quartile for 2023. Operating out of Chile, specifically from Santiago, the journal aims to converge its scope from 2019 to 2024 on providing high-quality, peer-reviewed articles that can inform and inspire academic and professional practices. While it is not an open-access journal, it remains a crucial outlet for impactful statistical research, fostering a deeper understanding of statistical concepts and their real-world applications.

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS is a distinguished journal published by Taylor & Francis Inc, dedicated to advancing the field of statistics through rigorous theoretical and methodological research. With an ISSN of 0361-0926 and an E-ISSN of 1532-415X, this journal serves as an essential platform for statisticians, researchers, and academics to disseminate their findings and engage in scholarly discourse. It covers a broad spectrum of topics within the realms of statistics and probability, maintaining its relevance in the academic community, as indicated by its prestigious Q3 category rank and Scopus percentile ranking of 51st in its field. Launched in 1976, the journal has been pivotal in shaping contemporary statistical methodologies up to 2024 and offers a robust archive of knowledge and insights, despite its non-Open Access status. By fostering high-quality peer-reviewed articles, COMMUNICATIONS IN STATISTICS-THEORY AND METHODS continues to play a vital role in the development and dissemination of statistical theory, making it indispensable for students and professionals striving to stay at the forefront of statistical science.

Statistica, an esteemed journal published by the Università degli Studi di Bologna, Dipartimento di Scienze Statistiche Paolo Fortunati, is a vital resource within the fields of statistical science and applied mathematics. Since its inception in 1969, this open-access journal has served as a platform for original research and comprehensive reviews, facilitating the dissemination of knowledge to a global audience. As of 2023, it is indexed in Scopus, holding a noteworthy position in the 43rd percentile in the realm of Decision Sciences and Statistics. Researchers and practitioners benefit from its focus on contemporary statistical methods, data analysis, and probability theory. With a commitment to fostering academic dialogue and collaboration, Statistica aims to highlight innovative findings and applications, ensuring that the community remains at the forefront of statistical advancements.

Japanese Journal of Statistics and Data Science, published by SPRINGERNATURE, is a leading academic journal dedicated to the advancement of statistical methodologies and data science applications, with a focus on fostering innovative research and discourse within the field. Since its inception in 2018, the journal has sought to bridge theory and practice, embracing emerging trends and interdisciplinary approaches that contribute to the ever-evolving landscape of statistics, probability, and computational theory. Hailing from Germany, the journal holds an impressive Q3 ranking in both Computational Theory and Mathematics and Statistics and Probability, reflecting its commitment to high-quality, impactful research. With an accessible ISSN of 2520-8756 and E-ISSN 2520-8764, the journal invites a global audience of researchers, professionals, and students to explore its rich array of articles and findings, all aimed at furthering knowledge and application in the realm of data science.