Statistical Analysis and Data Mining is a leading journal published by WILEY, dedicated to exploring the latest advancements in statistical methods and data mining techniques. With an ISSN of 1932-1864 and an E-ISSN of 1932-1872, this journal serves as a significant platform for researchers and professionals in statistical analysis, computer science applications, and information systems. Covering a wide range of topics from innovative analytical methodologies to emerging data mining algorithms, the journal aims to disseminate high-quality research that contributes to the evolving landscape of data science. Ranked in the Q2 category for the fields of Analysis, Computer Science Applications, and Information Systems in 2023, it emphasizes its relevance and impact within academia. While it offers limited Open Access options, the insights shared in this publication are integral for those wishing to stay ahead in fast-paced research and data-driven industries. Since its inception in 2008 and continuing through 2024, Statistical Analysis and Data Mining invites submissions that reflect rigorous empirical research coupled with practical implications, making it a vital resource for the academic community.

SIAM Journal on Mathematics of Data Science is an esteemed publication within the fields of applied mathematics and data science, published by SIAM PUBLICATIONS. This journal serves as a vital platform for researchers and practitioners, dedicated to disseminating high-quality research that addresses complex mathematical problems arising in the context of data science. The journal aims to bridge the gap between rigorous mathematical theory and practical applications, fostering interdisciplinary collaboration among mathematicians, data scientists, and statisticians. With its commitment to excellence, the SIAM Journal on Mathematics of Data Science contributes significantly to advancing the understanding and development of mathematical methodologies that analyze and interpret large datasets effectively. Researchers and professionals will find it an invaluable resource with its comprehensive articles, insightful reviews, and original research papers, which represent the forefront of innovative mathematical approaches in the evolving landscape of data science. For those interested in contributing to this dynamic field, the journal provides an array of access options tailored to diverse audiences.

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.

Statistics and Computing is a premier journal published by Springer, dedicated to advancing the fields of statistics and computational theory. With a strong focus on interdisciplinary research, this journal covers a broad spectrum of topics including, but not limited to, statistical methodologies, computational algorithms, and the latest advancements in data analysis. As of 2023, it proudly holds a Q1 ranking in multiple categories including Computational Theory and Mathematics and Statistics and Probability, underscoring its significant influence and recognition within the academic community. The journal's impact is further demonstrated by its commendable positions in Scopus ranks, making it a valuable resource for researchers, professionals, and students alike. Published in the Netherlands, Statistics and Computing is known for its rigorous peer-review process and commitment to quality, ensuring that only the most impactful research is disseminated to the global audience. Submissions from a diverse range of backgrounds are encouraged, fostering an inclusive environment for innovation and collaboration in the statistics and computing realm.

ENVIRONMENTAL AND ECOLOGICAL STATISTICS, published by SPRINGER, stands as a premier journal dedicated to advancing the fields of environmental science and statistical methodologies. With an ISSN of 1352-8505 and an E-ISSN of 1573-3009, this journal has continually provided a platform for innovative research and interdisciplinary studies since its inception in 1994. Operating from the Netherlands, it enjoys a significant impact within the academic community, reflected in its impressive Q2 rankings across various categories including Environmental Science and Statistics. The journal maintains a strong focus on the application of statistical techniques to ecological and environmental problems, fostering an environment for discourse that is both robust and insightful. Although it does not currently offer open access, the depth and quality of research published within its pages position it as a vital resource for researchers, professionals, and students alike, eager to understand and address the complexities of environmental data analysis up to the year 2024.

The Annals of Applied Statistics, published by the Institute of Mathematical Statistics (IMS), is a leading academic journal that serves as a crucial repository for groundbreaking research in the fields of statistics and probability applications. Since its inception in 2008 and continuing through 2024, this journal has established itself as an influential platform with a notable reputation, boasting a prestigious Q1 classification in 2023 across critical categories such as Modeling and Simulation and Statistics, Probability, and Uncertainty. With its rigorous peer-review process and significant Scopus rankings—including a position of #78 in Statistics and Probability—Annals of Applied Statistics aims to foster innovative statistical methods and their applications in a variety of disciplines. Researchers, professionals, and students interested in the latest advancements in analytical methods will find this journal essential for navigating the evolving landscape of applied statistics. The journal does not offer open access options, ensuring that published content reflects the highest academic standards.

Statistics and Applications is an esteemed academic journal dedicated to disseminating innovative research findings and advancements within the field of statistics and its diverse applications. Published by SOC STATISTICS COMPUTER & APPLICATIONS, this journal operates under an open access model, ensuring that critical knowledge and research are freely available to researchers, professionals, and students worldwide. With an ISSN of 2454-7395, it serves as a key platform for scholars to share their insights on statistical methodologies, computational techniques, and novel applications across various disciplines. Although the journal’s impact factor is not currently listed, its commitment to rigorous peer review and high-quality publications positions it as a valuable resource in the continuously evolving domain of statistics. By fostering collaboration among researchers and encouraging the sharing of knowledge, Statistics and Applications contributes significantly to the advancement of statistical science and its applications in real-world problems.

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.

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.

Statistical Methods and Applications is a leading journal published by SPRINGER HEIDELBERG, dedicated to advancing the field of statistics and its applications in various domains. With an ISSN of 1618-2510 and an E-ISSN of 1613-981X, this journal serves as a vital resource for researchers and professionals looking to explore innovative statistical methodologies and their practical implications. The journal has demonstrated a notable influence within the scholarly community, ranked Q3 in both Statistics and Probability and Statistics, Probability and Uncertainty categories as of 2023. Covering a scope that spans from its inception in 1996 to the present, Statistical Methods and Applications provides robust platforms for empirical studies, theoretical advancements, and applied statistics. Although currently not open access, the journal is well-regarded for its rigorous peer-review process and commitment to high-quality research, making it an essential read for anyone dedicated to enhancing their statistical knowledge and expertise.