Which of the following options could use both intercepts to produce viable solutions? (1 point)

To determine which of the options could use both intercepts to produce viable solutions, we need to understand what intercepts refer to in the context of a graph.

Intercepts are points where the graph intersects the axes, typically indicating values of one variable when the other variable is zero (x-intercept) or the value of the dependent variable when the independent variable is zero (y-intercept).

Let’s analyze each pair:

1. **(years of experience, starting salary)**:
- This relationship can produce a usable model since it is plausible to consider a scenario where someone with zero years of experience would have a starting salary (the y-intercept), and if someone achieves a high salary, it could reflect years of experience (the x-intercept).

2. **(age, weight)**:
- While there might be some relationship, it doesn’t lend itself well to meaningful intercepts since it doesn’t make sense to have a weight of zero for a person (age 0 could be considered but doesn't directly correlate in a linear sense with zero weight being viable).

3. **(temperature, number of car rentals)**:
- This could also produce a model where lower temperatures potentially lead to fewer rentals, but a temperature of absolute zero isn't realistic in practical terms for leading to viable car rentals (a paradoxical situation).

4. **(number of nominations, number of awards)**:
- This pair also makes sense; having zero nominations would suggest zero awards (y-intercept), and a considerable number of nominations could lead to an increased number of awards (x-intercept).

Based on this evaluation, the first (years of experience, starting salary) and the last (number of nominations, number of awards) options are the most viable for using both intercepts meaningfully for their respective variables. However, if we need to select one among the four that could use both intercepts, the best option is:

**(years of experience, starting salary)**.

This option clearly outlines a viable relationship that can produce both intercepts to generate meaningful solutions in a real-world context.