What is regression analysis primarily used for?

Regression analysis is primarily used to determine the relationship between variables. It involves statistical methods that allow analysts to model the relationships between a dependent variable and one or more independent variables. Through this analysis, it is possible to quantify how changes in the independent variables are associated with changes in the dependent variable, providing insights into both the strength and nature of the relationships.

This capability makes regression analysis a vital tool in various fields, including economics, finance, social sciences, and any area where data-driven decisions are made. By establishing these relationships, regression can help in forecasting outcomes, testing hypotheses, and informing strategic decisions based on empirical data.

The other options, while related to data and analysis, serve different purposes. For example, creating visual representations of data focuses on presenting information in a more digestible format rather than analyzing relationships. Segmenting market demographics deals with categorizing groups of consumers instead of evaluating how different factors interact with each other. Assessing project risks concerns identifying and analyzing potential obstacles in project management rather than directly evaluating variable relationships.