Statistical Modeling vs. Machine Learning Modeling: A Comparative Research

Ritambhara Jha

Abstract: Two strong techniques in modern data analysis are statistical modeling and machine learning (ML) modeling. A Statistical Model is the application of statistics to create a representation of data and then perform analysis to deduce any correlations between variables or uncover insights. Machine Learning is the application of mathematical and/or statistical models to get a broad knowledge of data in order to make predictions. While both strive to extract insights from data, their methodologies and objectives are very different. This research dives into the fundamental differences between these techniques, examining their advantages, disadvantages, and optimum application circumstances.

Keywords: Statistical Modeling, Machine Learning, Comparative Analysis, Predictive Modeling, Data Analysis, Hybrid Approaches, Interpretability