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.

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.

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.

Welcome to the Electronic Journal of Applied Statistical Analysis, a pivotal platform for researchers and practitioners in the domains of Statistics and Probability, as well as Modeling and Simulation. Published by Università del Salento in Italy, this journal has been dedicated to disseminating valuable insights and advancements in applied statistical methodology since its inception in 2008. With its ISSN of 2070-5948, the journal operates within an esteemed academic framework, contributing significantly to the field despite its current Q4 ranking in both Statistics and Probability and Modeling and Simulation categories as of 2023. As we continue to explore complex statistical models and simulation techniques, the journal encourages submissions that advance theoretical and practical understandings, inviting the global academic community to engage with transformative research endeavors. For those looking to stay informed and ahead in the dynamic world of applied statistics, the Electronic Journal of Applied Statistical Analysis is an essential resource.

Journal of the Royal Statistical Society Series A - Statistics in Society is a premier academic journal published by Oxford University Press, dedicated to advancing the understanding and application of statistical methods in the context of social issues. With an ISSN of 0964-1998 and an E-ISSN of 1467-985X, this journal has consistently been recognized for its high-quality contributions, reflected in its prestigious impact factors and quartile rankings. As of 2023, it holds a Q1 status in Social Sciences (miscellaneous) and notable Q2 rankings in Economics and Econometrics, as well as in Statistics and Probability, illustrating its influence and authority in the relevant fields. Researchers and professionals engaging with this journal can expect rigorous peer-reviewed articles, innovative methodologies, and comprehensive discussions that address contemporary statistical challenges within society. While currently not offering Open Access, the journal is committed to disseminating knowledge that enhances understanding of the interplay between statistics and social dynamics. Spanning from 1988 to 2024, the Journal of the Royal Statistical Society Series A remains a crucial resource for scholars looking to explore the vital intersection of statistical theory and societal applications.

Quantitative Methods for Psychology, with ISSN 1913-4126 and E-ISSN 2292-1354, is a premier open-access journal published by the University of Montreal, Department of Psychology. Since its inception in 2005, this journal has served as a vital resource for the dissemination of cutting-edge research and methodological advancements in psychological science. With a focus on quantitative approaches, it welcomes submissions that explore innovative statistical techniques, data analysis methodologies, and empirical studies that enhance understanding in psychology. The journal’s commitment to accessibility ensures that researchers, practitioners, and students alike can benefit from the wealth of knowledge it offers, fostering collaboration and advancing the field. As an integral platform for sharing significant findings and best practices, Quantitative Methods for Psychology is positioned to make substantial contributions to the landscape of psychological research.

LIFETIME DATA ANALYSIS, published by Springer, stands as a premier journal within the fields of Applied Mathematics and Medicine, with an impressive Q1 category ranking in both disciplines as of 2023. Established in 1995, this journal specializes in the analysis of time-to-event data and related methodologies, providing valuable insights applicable to clinical trials, epidemiology, and survival analysis. With its aim to foster innovative research that enhances statistical methods, LIFETIME DATA ANALYSIS supports the academic community by publishing high-quality articles that cover both theoretical advancements and practical applications. Although it does not offer open access, this journal reaches a wide audience globally, bridging the gap between mathematics and health sciences, and underlining its essential role in advancing interdisciplinary research.

Statistics in Medicine, published by Wiley, is a prestigious journal dedicated to the advancement of statistical methods and their application in biomedical research. Established in 1982, this journal has become a cornerstone in the fields of Epidemiology and Statistics and Probability, demonstrating its importance by consistently achieving a Q1 ranking in the 2023 category quartiles. With an impressive ISSN of 0277-6715 and an E-ISSN of 1097-0258, it serves as a vital platform for disseminating high-quality research that enhances evidence-based medicine. Although the journal does not currently offer open access, it remains highly regarded, holding a Scopus rank of #66 in Mathematics and #80 in Medicine, indicating its significant impact on the academic community. By publishing cutting-edge research, Statistics in Medicine aims to bridge the gap between statistical theory and practical application in health domains, fostering a rigorous dialogue among researchers, clinicians, and statisticians alike.

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.

Electronic Journal of Statistics, published by INST MATHEMATICAL STATISTICS-IMS, is a premier open-access platform dedicated to the field of statistics and probability, with a remarkable track record since its inception in 2007. With an ISSN of 1935-7524, this journal has quickly established itself as a leading resource within the top Q1 category in both Statistics and Probability, as well as Statistics, Probability and Uncertainty, highlighting its significance and impact in the academic community. The journal’s commitment to disseminating high-quality research allows researchers, professionals, and students to access valuable findings and methodologies that contribute to the advancement of statistical sciences. With its convergence set to continue until 2024, the Electronic Journal of Statistics remains a vital source for scholars looking to enrich their knowledge and engage with cutting-edge statistical theories and applications.