What type of analysis quantifies the relationship between a dependent variable and one or more independent variables?

Regression analysis is a statistical method used to quantify the relationship between a dependent variable and one or more independent variables. This technique allows researchers and decision-makers to understand how changes in the independent variables can impact the dependent variable, which is crucial for making informed decisions based on data.

Through regression analysis, you can derive equations that predict the dependent variable's values from the values of the independent variables. This is particularly useful in various fields such as finance, economics, social sciences, and any discipline where predicting outcomes based on variables is essential. For example, a business could use regression analysis to understand how advertising spend (independent variable) affects sales revenue (dependent variable).

The other options do not specifically focus on quantifying relationships in the same way. Reliable data refers to the quality and trustworthiness of data, which is important for analysis but does not describe a method for analyzing relationships. Random variation pertains to the inherent unpredictability in data, which does not provide a structured approach to analyzing relationships. Results-based management is a framework for improving decision-making and accountability but does not specifically quantify relationships between variables like regression analysis does.