To determine which pairs of variables could use both intercepts to produce viable solutions, we need to consider whether the quantities can realistically intersect at certain points in a hypothetical graph.
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(age, weight): These can intersect, but there are no specific intercept points relevant to this context, making it less likely to be viable.
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(temperature, number of car rentals): Temperature can affect the number of car rentals, which may have intersecting points where a certain temperature leads to a certain number of rentals, making this a viable option.
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(number of nominations, number of awards): These two variables may also intersect, as nominations typically lead to awards. This is another viable option.
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(years of experience, starting salary): This relationship often does not have meaningful intercept points (you usually can't have a starting salary or years of experience as zero in a realistic sense).
Based on this analysis, the pairs (temperature, number of car rentals) and (number of nominations, number of awards) could use both intercepts to produce viable solutions. Therefore, if selecting one, (temperature, number of car rentals) might be the best example of a relationship where both intercepts could be utilized meaningfully.
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