DISTRIBUTION THEORY APPLICATIONS IN STATISTICAL MODELING
SIRAJUDDEEN. P. K
STATISTICS
May 2024
Distribution theory is a fundamental tool in statistics, providing fundamental tools for understanding random variable behavior and probability distributions. Key concepts like probability distributions, moments, the central limit theorem, and conditional distributions are used in hypothesis testing, parameter estimation, and predictive modeling. These methods help researchers assess observed differences, determine unknown parameters in statistical models, and guide decision-making in finance, epidemiology, engineering, and beyond. Distribution theory is relevant in characterizing asset returns, modeling disease spread, and analyzing system reliability. However, challenges like modeling non-Gaussian distributions and handling high-dimensional data persist. Future research should focus on advancing distributional models, integrating with machine learning techniques, and exploring applications in emerging fields. Addressing these challenges can enhance the efficacy of statistical modeling techniques across diverse domains.
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