What is regression analysis primarily used for?

Regression analysis is primarily used to determine the relationship between variables, making it a powerful statistical method for understanding how one or more independent variables affect a dependent variable. This technique is widely utilized in various fields, including economics, psychology, and social sciences, to model the relationships and quantify the strength of the associations.

In regression analysis, a mathematical equation is created that captures the nature of the relationship, which can then be used for prediction. By analyzing the coefficients of the regression model, it is possible to assess the extent to which each independent variable influences the dependent variable, thus enabling insights into causal relationships.

For instance, in a business context, regression analysis might be employed to understand how advertising expenditure impacts sales revenue. By knowing this relationship, businesses can make informed decisions about budget allocation.

Other options, while useful in their own right, do not serve the primary purpose of regression analysis. Summarizing data, visualizing distribution, and identifying outliers are essential activities in data analysis but are not the focus of regression techniques.