Focus & Scope

Mathematica: Journal of Applied Mathematics, Statistics, and Probability

Focus
Mathematica: Journal of Applied Mathematics, Statistics, and Probability is committed to advancing research and innovation in the application of mathematics, statistics, and probability in solving real problems across multiple disciplines. The journal's primary goal is to publish high-quality research that demonstrates the application of mathematics, statistics, and probability theory in fields such as science, engineering, economics, health, and the environment. With a focus on analytic and computational-based solutions, the journal aims to be a platform for researchers, academics, and practitioners to share insights, methodologies, and innovative applications in applied mathematics, statistics, and probability.

Scope
The journal covers a wide range of topics in applied mathematics, statistics, and probability, including, but not limited to:

1. Mathematical Models: Development and analysis of mathematical models for physical, biological, financial, and social systems.
2. Numerical and Computational Analysis: The study of numerical algorithms for the solution of differential equations, optimization, and computational simulation.
3. Applied Statistics: Application of statistical methods in data collection, analysis, interpretation, and presentation of data in real contexts.
4. Applied Probability: The study of probability theory and stochastic processes in uncertainty and risk modeling.
5. Optimization and Operations Research: Development and application of optimization techniques in decision making, planning, and resource allocation.
6. Data Science and Big Data Analytics: Application of applied mathematics and statistics in big data analytics, machine learning, and artificial intelligence.
7. Bayes Statistics and Statistical Inference: Research on the Bayes approach in parameter estimation and hypothesis testing.
8. Decision and Game Theory: A study of mathematical models in strategic decision making and game theory.
9. Real-time and Time Series Data Analysis: The use of statistical and mathematical methods in the analysis of data that changes over time.
10. Bioinformatics and Biostatistics: Applications of applied mathematics and statistics in biology and medicine, including genomic analysis and epidemiology.