1. A financial analyst theorizes that commute × increase as the percentage of land availability for homes in a city decreases. To test this hypothesis, the analyst uses a regression analysis to explore how land availability predicts commute time. What does land availability represent in this regression?
Answer: B
Land availability represents the independent variable in this regression analysis.
In this context, land availability is being used to predict commute time, which indicates that it serves as the independent variable in the regression analysis.
A) It is the dependent variable.
This option is incorrect because the dependent variable is the one being predicted or explained in a regression analysis. In this scenario, commute time is the dependent variable, not land availability.
B) It is the independent variable.
This option is correct as land availability is used to predict changes in commute time. In regression analysis, the independent variable is the one that influences or affects the dependent variable, which aligns with the analyst's hypothesis.
C) It is the target variable.
While the term "target variable" can sometimes refer to the dependent variable, in this case, it is misleading. Land availability is not the target being predicted; rather, it is the variable that is expected to influence the outcome (commute time).
D) It is a control.
This option is incorrect because a control variable is one that is held constant to prevent it from influencing the outcome. Land availability is not being controlled but rather tested for its effect on commute time, making it the independent variable.
Conclusion
Land availability is definitively the independent variable in this regression analysis, as it is used to predict the dependent variable, which is commute time. All other options fail to accurately describe the role of land availability in the context of this analysis, confirming that it influences the outcome rather than being predicted by it.