Aim

Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics (Commun. Fac. Sci. Univ. Ank. Ser. A1. Math. Stat.) is an international peer-reviewed journal dedicated to the publication of high-quality research articles in all areas of pure and applied mathematics and statistics. The journal aims to provide a platform for the dissemination of original and significant contributions that advance theoretical understanding and practical applications in these fields.

Scope

The scope of Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics includes, but is not limited to:

• Pure mathematics: algebra, analysis, geometry, topology, number theory, mathematical logic, fuzzy logic
• Applied mathematics: numerical analysis, optimization, differential equations, mathematical physics, mathematical modeling
• Probability and statistics: theoretical statistics, statistical modeling, data analysis, stochastic processes, biostatistics, operation research, and econometrics
• Interdisciplinary research that connects mathematics or statistics with other scientific disciplines such as machine learning, pattern recognition, clustering etc.

The journal welcomes both theoretical developments and innovative applications. It supports the exchange of ideas among researchers worldwide and encourages submissions that bridge the gap between theory and practice.

Readership

Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics journal primarily targets researchers, academics, postgraduate, and doctoral students working in the fields of mathematics and statistics, as well as anyone interested in staying updated on current developments in these disciplines. The articles we publish are particularly relevant to specialists in the following areas:

• Mathematics: Analysis, algebra, geometry, topology, applied mathematics, numerical analysis, and mathematical modeling.
• Statistics: Theoretical statistics, applied statistics, probability theory, biostatistics, econometrics, data science, and machine learning.

Period Months