To determine which options could use both intercepts to produce viable solutions, we need to analyze the pairs in terms of how they can be represented on a graph with two variables:
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(age, weight): Both age and weight can take on zero values, making this a suitable option where we could possibly have intercepts at (0,0).
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(temperature, number of car rentals): Temperature can be zero, though the number of car rentals cannot logically be zero in some contexts, causing difficulties in interpreting intercepts.
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(number of nominations, number of awards): This pair also struggles since the number of nominations can be zero, which allows for analysis, but interpreting awards against nominations might not produce a clear intercept scenario since winning awards is typically a dependent statistic on nominations.
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(years of experience, starting salary): Both years of experience and starting salary could realistically be zero, allowing for potential intercepts at (0,0), making this a viable scenario.
Based on this analysis, the options that could use both intercepts to produce viable solutions are (age, weight) and (years of experience, starting salary). If you can only select one option, then (years of experience, starting salary) is a clear practical choice for intercept analysis.
Overall, options (age, weight) and (years of experience, starting salary) are the most viable.
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