Which method is used to model the relationship between dependent and independent variables?

The correct choice is regression analysis because it specifically aims to model and quantify the relationship between one or more independent variables and a dependent variable. This technique helps in understanding how changes in the independent variables impact the dependent variable, allowing researchers to make predictions and understand the dynamics within the data.

For example, in a business context, regression analysis can be used to assess how factors like advertising expenditure, pricing, and economic conditions influence sales figures. It provides insights into the strength and nature of these relationships, whether they are positive, negative, or non-linear.

In contrast, correlation analysis focuses on quantifying the strength and direction of the relationship between two variables without implying causation. Descriptive statistics summarize and describe the characteristics of a dataset but do not analyze relationships between variables. Inferential statistics use sample data to make generalizations about a larger population, but they are not specifically aimed at modeling dependencies between variables. Thus, regression analysis is the most appropriate method for this purpose.