Which of the following statements is false regarding regression analysis?

In regression analysis, the primary function is to understand relationships between variables, and while it can suggest associations and correlations between independent and dependent variables, it does not definitively establish cause-and-effect relationships. This distinction is crucial because correlation does not imply causation; just because two variables show a relationship does not mean that one causes the other. For instance, a regression analysis might show that there is a correlation between ice cream sales and temperature, but it cannot be concluded that increased ice cream sales cause the temperature to rise.

The other statements hold true within the context of regression analysis. It does identify correlation between variables, which is integral to its utility. Regression is also utilized to make predictions about dependent variables based on the values of independent variables, and it typically operates under the assumption of a linear relationship between those variables unless otherwise specified in a more advanced non-linear regression model. Each of these elements contributes to the overall understanding and application of regression analysis in data interpretation and prediction.