AUSRALIAN & NEW ZEALAND JOURNAL OF STATISTICS, published by Wiley, stands as a significant platform for the dissemination of statistical knowledge and applications, specifically within the realms of statistics and probability. With an impact factor reflective of its quality and standing, the journal operates in a Q3 category for both Statistics and Probability, as well as Statistics, Probability, and Uncertainty, positioning it among the important scholarly resources in its field. As a valuable resource for researchers, professionals, and students, the journal encourages the submission of innovative research articles that push the boundaries of statistical science. Offering both print and open access options, it ensures broad accessibility, promoting a culture of collaboration and knowledge sharing across the global statistical community. Covering research from 1998 to 2024, it remains dedicated to advancing understanding in statistical methodologies and their applications, cementing its role in fostering academic discourse and practical advancements in the field.

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.

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.

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.

SOFTWARE QUALITY JOURNAL, published by Springer, is a preeminent platform dedicated to advancing the field of software engineering and quality assurance. With an ISSN of 0963-9314 and an E-ISSN of 1573-1367, this journal serves as a vital resource for academics and practitioners alike, bridging the gap between theoretical frameworks and practical applications. The journal is recognized for its impactful contributions, holding a remarkable Q1 ranking in Media Technology and demonstrating strong performance with Q2 placements in Safety, Risk, Reliability and Quality, as well as Software, solidifying its reputation in the academic community. As of 2023, the journal is ranked 64th in Safety, Risk, Reliability and Quality and 176th in Computer Science Software on Scopus, showcasing its relevance and influence. Covering a broad range of topics from software quality metrics to risk management strategies, SOFTWARE QUALITY JOURNAL aims to foster innovation and best practices in software development. Join a community of leading researchers and professionals committed to enhancing the quality and reliability of software systems.

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.

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.

Sankhya-Series B: Applied and Interdisciplinary Statistics, published by Springer in India, serves as a vital platform for advancing the field of applied statistics and interdisciplinary research. With an ISSN of 0976-8386 and an E-ISSN of 0976-8394, this journal has made significant contributions since its inception in 2010, continuing to publish impactful research until 2024. The journal is ranked in the third quartile across several categories, including Applied Mathematics and Statistics, reflecting its importance within the academic community. Although not an open-access journal, Sankhya-Series B provides robust access options for its readership, facilitating the dissemination and discussion of critical statistical methodologies and applications. Researchers, professionals, and students are encouraged to engage with the journal's comprehensive scope, which includes a focus on statistical theory, methodologies, and their practical applications across various disciplines. By providing a rigorous forum for scholarly exchange, this journal plays an essential role in shaping the future of applied statistics and fostering interdisciplinary collaboration.

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.

STATISTICAL MODELLING, published by SAGE Publications Ltd in the United Kingdom, is a prominent peer-reviewed journal dedicated to the evolving domain of statistics and its application in various scientific fields. With the ISSN 1471-082X and E-ISSN 1477-0342, this journal serves as a vital platform for researchers and practitioners to disseminate innovative methodologies, theoretical advancements, and practical applications pertaining to statistical modelling. Covering research from 2001 to 2024, the journal consistently contributes to the discourse within the Q3 quartile in both Statistics and Probability and Statistics, Probability and Uncertainty categories. Furthermore, it ranks in the 54th percentile for Mathematics - Statistics and Probability and in the 53rd percentile for Decision Sciences, reflecting its growing reputational value among academic peers. Although this journal does not include Open Access options, its rigorous selection process and scholarly contributions ensure that it remains an essential resource for statistical research. Researchers, professionals, and students alike will find STATISTICAL MODELLING to be an indispensable reference for advancing their understanding and application of statistical techniques.