Publisher
Journal Description
Statistics is a leading international, peer-reviewed academic journal published by Taylor & Francis, dedicated to advancing research in the field of statistics and statistical science. With a long-standing publication history dating back to 1985, the journal has established itself as a reputable platform for disseminating high-quality scholarly work in both theoretical and applied statistics. It attracts contributions from researchers worldwide and maintains rigorous editorial standards to ensure the publication of scientifically sound and impactful studies.
The journal emphasizes originality, mathematical rigor, and practical relevance, publishing research that contributes meaningfully to the development of statistical methodologies and their applications. Through a structured peer-review process and adherence to high ethical standards, Statistics ensures the integrity and quality of its published content, making it a valuable resource for statisticians, mathematicians, and interdisciplinary researchers.
Aims and Scope
The primary aim of Statistics is to publish innovative research that advances statistical theory, methods, and applications across a wide range of disciplines. The journal focuses on contributions that demonstrate strong theoretical foundations supported by rigorous mathematical proofs, as well as applied research that effectively utilizes statistical techniques to address real-world problems. It does not consider studies lacking theoretical significance or those with purely descriptive applications without methodological contribution.
The scope of the journal includes diverse areas such as statistical learning, machine learning, nonparametric statistics, functional data analysis, time series, network models, econometrics, psychometrics, survival analysis, and risk management. It also welcomes research on the evaluation of artificial intelligence applications from a statistical perspective. By promoting both theoretical advancements and practical implementations, Statistics supports the continuous evolution of modern statistical science and its role in data-driven decision-making.