What does regression analysis estimate?

Regression analysis is a powerful statistical method used to examine the relationships between variables. Specifically, it is employed to understand how the dependent variable (often referred to as the response variable) changes when one or more independent variables (predictors) are varied. By analyzing these relationships, regression enables the estimation of expected values of the dependent variable based on known values of the independent variables.

This method provides insights into the strength and direction of the relationships, allowing researchers and analysts to make predictions and informed decisions based on the data. For example, in business contexts, regression analysis might help in assessing how changes in advertising spending (independent variable) affect sales revenue (dependent variable).

In contrast, other options reflect different statistical concepts. Estimating the mean pertains to central tendency, frequency of occurrences relates to probability distributions, and standard deviation is a measure of variability. These aspects do not capture the relationship-based focus characteristic of regression analysis, further emphasizing why estimating relationships among variables is the correct interpretation of what regression analysis does.