Statistical modeling is a mathematical approach used to represent complex data and relationships within various fields, including social science. It helps researchers analyze patterns, make predictions, and understand underlying structures in data. By using statistical techniques, social scientists can quantify relationships between variables, such as income and education levels. Causal inference is a method used to determine whether a change in one variable directly causes a change in another. In social science, this is crucial for understanding the impact of policies or interventions. By combining statistical modeling with causal inference, researchers can draw more reliable conclusions about social phenomena and inform decision-making.