Mathematical Statistics
Mathematical Statistics encompasses the use of mathematical models and statistical methods to analyze data in the context of scientific research, computer science applications, and chemical experiments. It involves the development of theories, algorithms, and computational techniques for modeling uncertainty, making predictions, and testing hypotheses. This subfield brings together concepts from probability theory, calculus, linear algebra, and discrete mathematics with an emphasis on statistical inference, machine learning, and data analysis to advance knowledge in Sciences, Computer Science and Chemistry. Mathematical Statistics addresses questions concerning the design of experiments, estimation of parameters, hypothesis testing, Bayesian inference, time series analysis, multivariate methods, and non-parametric statistics among others. By combining mathematical rigor with empirical research, this subcategory serves as a powerful tool for understanding complex phenomena and making informed decisions in these domains.