To determine which of the given options could use both intercepts to produce viable solutions, we should consider the nature of the variables involved in each option.
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(temperature, number of car rentals) - Temperature can influence the number of car rentals. Each variable can be measured in a way that allows for a potential intercept (e.g., zero temperature, zero rentals). Viable solutions can exist.
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(number of nominations, number of awards) - This relationship is somewhat dependent, as more nominations typically lead to more awards. However, having zero nominations does not realistically produce a viable solution related to awards. The model might not have a practical scenario where both variables truly intersect at the origin.
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(years of experience, starting salary) - It's reasonable to expect that with zero years of experience, the starting salary could also be zero (or very low). This suggests that both variables could intersect and provide viable solutions.
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(age, weight) - Age and weight have a complex relationship, and there is no logical scenario where both variables would yield a viable solution intersecting at the origin (considering age cannot logically be zero if we are talking about human age, and weight being zero is unrealistic).
Based on the analysis, the options that could use both intercepts to produce viable solutions are:
- (temperature, number of car rentals)
- (years of experience, starting salary)
However, since the question asks for one option, the strongest candidates are (years of experience, starting salary), as it firmly relates to a career progression model where intercepts are more applicable.