Final answer:
Regression analysis does not prove causation. It identifies correlations between variables that can be a starting point for further investigation. The statement is false.
Step-by-step explanation:
False
Regression is a statistical technique used to measure the nature of relationships between variables, such as cause and effect. It helps determine the strength and direction of causality between a dependent (effect) variable and one or more independent (causal) variables.
However, regression analysis does not prove causation. It only identifies correlations between variables, which can be a starting point for further investigation.
Regression is not a method to definitively determine whether one thing causes another; it is a statistical tool used to model the relationship between variables. In geographic analysis, regression analysis might show the relationship between the number of fast-food joints and obesity rates, but this does not prove causation.
There are often other factors, like ethnicity, income, and access to parks, which might also influence obesity. Variables in regression analysis can sometimes be confounded by other external factors, which means that even a significant regression does not imply causation.