Final answer:
The independent variable is the age of the car, while the dependent variable is the resale value of the car. Regression analysis and scatter plots are commonly used to analyze the negative relationship where older cars tend to have lower resale values.
Step-by-step explanation:
In the context of predicting the resale value of a car based on its age, the explanatory variable, also known as the independent variable, is the age of the car, as it is the factor that is presumed to influence the outcome. The response variable, or the dependent variable, is the resale value of the car, which is expected to be affected by the car's age. This setup is typical in regression analysis, where the goal is to model the relationship between variables and often entails creating a scatter plot or calculating a regression line to assess the nature of the relationship. In this case, you would expect to see a negative relationship depicted in a scatter plot, where the cars of greater age tend to have lower resale values.
Furthermore, the dependent variable is used to show or disprove causation between two variables, as it responds to changes in the independent variable. For instance, in the used car scenario, if the analysis shows a strong negative correlation between car age and resale value, this may indicate that as cars get older, they are likely to be valued less, thus supporting the causation hypothesis.