Which statistical method examines the relationship between one or more independent variables and a dependent variable?

The appropriate statistical method for examining the relationship between one or more independent variables and a dependent variable is regression analysis. This technique is widely used in statistics to model and analyze the relationships between variables. In regression analysis, the independent variable(s) are used to predict or explain variations in the dependent variable.

Regression analysis can be simple, involving a single independent variable, or multiple, incorporating several independent variables. The primary goal is to ascertain the nature of the relationships and quantify how changes in the independent variables affect the dependent variable by providing estimates of the coefficients that define the linear relationship.

This method is foundational in various fields, including economics, biology, engineering, and social sciences, where understanding how different factors influence a particular outcome is crucial. It provides insights that can be used for prediction and decision-making.

The other choices do not serve this function: the automated valuation model is primarily used in real estate for property valuation, the standard error of the mean measures the dispersion of sample means, and error analysis evaluates mistakes in models rather than examining relationships.