JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS is a premier academic publication dedicated to advancing the fields of computational statistics and graphical data representation. Published by Taylor & Francis Inc, this journal stands out with its impressive Q1 rankings in Discrete Mathematics and Combinatorics, Statistics and Probability, and Statistics, Probability and Uncertainty, reflecting its high impact and relevance in contemporary research. Since its inception in 1992, the journal has been a vital resource for researchers, professionals, and students alike, with its rigorous peer-reviewed articles contributing significantly to the science of data analysis and visualization. With a Scopus ranking placing it within the top tiers of its category, the journal is committed to disseminating high-quality research that promotes innovation and methodological advancement. Note that the journal currently follows a traditional subscription model, ensuring focused and curated content for its readers. As it approaches the horizon of 2024, the JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS continues to foster scholarly discourse and discoveries, making it an essential platform for anyone involved in statistics and data science.

The Journal of Official Statistics, published by SAGE Publications Inc, is a premier open-access journal that has been fostering advancements in the field of statistics since its inception. With its focus on disseminating high-quality research from 1986 to present, this journal provides a vital platform for statistical practices, innovations, and methodologies applicable to various domains, including governmental and organizational data analysis. Recognized as a Q2 journal in the Statistics and Probability category with a Scopus ranking of #143 out of 278, the Journal of Official Statistics boasts a significant impact in informing statisticians and practitioners alike. Located in Sweden, this journal has embraced open access since 2013, ensuring that its comprehensive and research-driven content is accessible to a global audience. Whether you are a researcher, professional, or student, this journal serves as an essential resource for staying informed about the latest trends and discussions in the official statistical 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.

ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS, published by SPRINGER HEIDELBERG, is a prestigious academic journal that has played a pivotal role in the field of statistical mathematics since its inception in 1949. With a focus on advancing research in statistics and probability, this journal is ranked in the Q2 quartile for 2023, indicating its significance and impact within the academic community. Researchers and professionals engaged in statistical theory and methodology will find the journal's comprehensive coverage of contemporary issues essential for furthering their work and understanding of the discipline. The journal is accessible in print and digital formats, facilitating wide dissemination of knowledge among its readership. With a history of rigorous peer review and a commitment to high-quality research, the ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS continues to be a vital resource for academics and practitioners alike.

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.

Thailand Statistician, published by the THAI STATISTICAL ASSOCIATION, is a pivotal journal in the realms of computational mathematics and statistics. With an ISSN of 1685-9057 and an E-ISSN of 2351-0676, this journal aims to disseminate high-quality research and innovative methodologies that advance the fields of statistics and probability. Covering a range of topics from theoretical statistics to applied computational techniques, it provides a platform for researchers, professionals, and students in Thailand and beyond to contribute their findings and insights. The journal has been gaining recognition, boasting a Scopus ranking of Q3 in Computational Mathematics and Q4 in Statistics and Probability as of 2023. With its commitment to open access, the Thailand Statistician stands as an essential resource for those striving to stay abreast of advancements in statistical methodologies and their applications, fostering the growth of statistical science in the region and globally.

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.

Korean Journal of Applied Statistics, published by the Korean Statistical Society, is a prominent journal dedicated to advancing the field of applied statistics. ISSN 1225-066X (Print) and E-ISSN 2383-5818 (Online), this journal serves as a vital platform for disseminating high-quality research that addresses the latest methodologies, applications, and innovations in statistical practices. Though currently not an open-access journal, it aims to foster collaboration among statisticians, researchers, and practitioners by providing rigorous peer-reviewed articles that enhance understanding and application of statistical techniques across various disciplines. With a commitment to integrating theory and practice, the Korean Journal of Applied Statistics stands as a crucial resource for those seeking to influence the evolving landscape of statistical research and its applications in Korea and beyond.

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.