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.

BIOMETRICS, published by WILEY, stands as a prestigious journal that has made substantial contributions across diverse fields, including Agricultural and Biological Sciences, Applied Mathematics, and Biochemistry. With an impressive track record from its inception in 1946 and continuing through to 2024, this journal is recognized for its rigorous peer-reviewed research and high-impact findings, evidenced by its Q1 ranking in various categories such as Medicine and Statistics. Researchers and professionals alike will find a wealth of knowledge within its pages, making it an essential resource for anyone involved in these dynamic and evolving disciplines. While BIOMETRICS does not offer open access, its reputation for delivering high-quality research ensures its continued importance in advancing the scientific ecosystem. For those seeking to stay ahead in their fields, engaging with the latest studies published in this journal is indispensable.

Intelligent Data Analysis is a highly regarded journal published by IOS Press, specializing in the fields of Artificial Intelligence, Computer Vision, and Pattern Recognition. With its ISSN 1088-467X and E-ISSN 1571-4128, the journal has been a cornerstone of scholarly communication since its inception in 1997, serving as a vital resource for researchers, professionals, and students engaged in advancing methodologies and applications in intelligent data analysis. The journal maintains its significance with impressive Scopus ranks, indicating its notable position within the academic community. Although currently not an Open Access journal, Intelligent Data Analysis offers a wealth of insights and findings, encouraging collaboration and knowledge exchange among its readership. With an impact factor reflective of its rigorous selection processes, the journal traverses a broad range of topics, contributing to ongoing discussions and innovations in its field. As the journal looks toward shaping future research until 2024 and beyond, it remains a pivotal platform for disseminating cutting-edge research and fostering academic inquiry.

Statistics in Biosciences is a distinguished journal published by Springer, focusing on the innovative interplay between statistical methodologies and biosciences. Established in 2009, this journal aims to provide a platform for the dissemination of cutting-edge research in statistical applications within biochemistry, genetics, and molecular biology. With an impressive impact factor and a distinguished ranking in multiple categories, including Q2 in Biochemistry, Genetics and Molecular Biology (miscellaneous) and Q3 in Statistics and Probability, it serves as a crucial resource for researchers, professionals, and students seeking to deepen their understanding of statistical applications in biological contexts. The journal is accessible through traditional subscription models, ensuring that high-quality research remains available to a wide audience. Featuring contributions that advance statistical theory and application in the biosciences, Statistics in Biosciences is committed to fostering collaboration and innovation in a rapidly evolving scientific landscape.

Applied Stochastic Models in Business and Industry, published by Wiley, is a preeminent journal dedicated to advancing the field of stochastic modeling in various business and industry contexts. With an ISSN of 1524-1904 and an E-ISSN of 1526-4025, this journal serves as a vital platform for researchers and practitioners aiming to leverage stochastic techniques to address complex decision-making and operational challenges. The journal holds prestigious rankings, including Q2 in Business, Management and Accounting, and has converged years spanning from 1999 to 2024. It is distinguished by its wide scope, focusing on all aspects of modeling and simulation, as well as decision sciences and operations research. Although it does not operate as an open-access journal, its significant impact factor and Scopus rankings ensure that the valuable insights published within reach a broad audience. By fostering high-quality research and discourse, Applied Stochastic Models in Business and Industry plays a crucial role in driving innovation and excellence in its fields.

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.

BIOMETRICAL JOURNAL is a prestigious academic publication dedicated to advancing the fields of Medicine and Statistics. Published by WILEY since its inception in 1977, this journal plays a critical role in disseminating cutting-edge research and methodologies that bridge the gap between statistical theory and real-world medical applications. With an impressive Q1 ranking in both Medicine (miscellaneous) and Statistics, Probability and Uncertainty, it is recognized for its high-impact contributions to the scientific community. The journal actively encourages submissions that utilize innovative statistical techniques to address complex biomedical issues, making it an essential resource for researchers, professionals, and students aiming to enhance their understanding of quantitative approaches in health and medicine. Although the journal is not open access, its rigorous peer-review process guarantees the quality and relevance of published works, further establishing its significance in the academic landscape.

Wiley Interdisciplinary Reviews: Computational Statistics is a leading journal published by WILEY, renowned for its influential contributions to the field of statistics and its application in computational studies. With an impressive impact factor reflected in its 2023 categorization as Q1 in Statistics and Probability, this journal ranks among the top in its category, positioned at 20 out of 278 in Scopus, placing it in the 92nd percentile for its discipline. The journal spans from 2009 to 2024 and offers a rich repository of interdisciplinary insights that encompass both theoretical advancements and practical applications of computational statistics, making it an invaluable resource for researchers, professionals, and students alike. While it does not currently offer open access, the journal's commitment to high-quality, peer-reviewed content ensures that it remains a trusted source for cutting-edge developments and methodologies in the rapidly evolving realm of computational statistics.

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.

Spatial Statistics is a premier journal published by ELSEVIER SCI LTD, focusing on innovative methodologies and applications in the realm of statistical analysis within spatial contexts. With an ISSN of 2211-6753, the journal has established itself as a significant contributor in its field since its inception in 2012, and continues to thrive, with its next volume projected through 2024. It holds a respectable Q2 ranking across several categories, including Computers in Earth Sciences, Management, Monitoring, Policy and Law, and Statistics and Probability, affirming its impact and relevance to researchers and professionals alike. The journal's commitment to publishing high-quality research enables scientists to advance understanding of spatial phenomena, facilitating informed decision-making in various applications ranging from environmental science to urban planning. As part of a robust academic community, Spatial Statistics invites submissions that push the boundaries of conventional statistical techniques, ensuring that the latest findings contribute significantly to the discipline's body of knowledge.