STATISTICAL MODELING: FOUNDATIONS APPLICATIONS AND INTERPRETATION

Statistical modeling is a fundamental approach in data analysis that constructs mathematical representations of observed data to explain relationships, make predictions, and support decision‑making under uncertainty. It integrates probability theory with computational techniques to interpret variability in complex systems across science, engineering, economics, and social sciences. This article reviews the principles of statistical modeling, common methodologies, and practical applications. It highlights how models are specified, estimated, and validated and discusses their importance in extracting meaningful insights from data.