What is regression analysis used for?

Regression analysis is a statistical method specifically used to examine the relationship between dependent and independent variables. It enables researchers and analysts to understand how the changes in one or more independent variables impact the dependent variable. This relationship can help in identifying trends, patterns, and associations within data, which is crucial for making informed decisions.

For instance, in a business context, regression analysis might be used to understand how advertising spend (independent variable) affects sales revenue (dependent variable). By quantifying this relationship, businesses can predict future sales based on different levels of advertising expenditure.

Other choices relate to different aspects of data analysis. Analyzing the frequency of data records pertains more to descriptive statistics than regression, while grouping large datasets involves clustering techniques, which are distinctly different from regression. Predicting future data storage needs is more associated with forecasting rather than regression analysis specifically. Thus, understanding the interplay of dependent and independent variables is the primary purpose of regression analysis, making that answer the most appropriate in this context.