Question

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

(number of nominations, number of awards)
(number of nominations, number of awards)

(age, weight)
(age, weight)

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

(temperature, number of car rentals)

Answer 1

Which of the following examples represents a discrete data constraint with viable solutions?(1 point)
Responses

average score on a test
average score on a test

number of tests passed
number of tests passed

average weight of all the newborns in a hospital ward
average weight of all the newborns in a hospital ward

distance between points

Answer 2

To identify which of the options could use both intercepts to produce viable solutions, we need to consider the context of the variables involved in each pair:

1. **(number of nominations, number of awards)**: This pair makes sense, as the number of nominations could be plotted against the number of awards. The intercepts could represent scenarios where there are nominations but no awards or vice versa.

2. **(age, weight)**: Age and weight can vary independently of each other, and while they can be plotted together, the concept of intercepts may not hold meaningful interpretations for these two variables.

3. **(years of experience, starting salary)**: This relationship is common in labor economics, and both intercepts can represent meaningful solutions (e.g., salary at zero years of experience, or an experience level at which salary trends can be analyzed).

4. **(temperature, number of car rentals)**: This relationship can also potentially have viable solutions, as temperatures can affect rental behavior. However, the specific nature of this intercept relationship might be less direct than the previous options.

Given this analysis, the strongest candidates for using both intercepts to produce meaningful solutions are:

- **(number of nominations, number of awards)**
- **(years of experience, starting salary)**

Both of these options can provide useful insights and interpretations from the intercepts in a relevant context.

Therefore, the best responses could be **(number of nominations, number of awards)** and **(years of experience, starting salary)**. If you need to select just one, then **(years of experience, starting salary)** would be my choice.

Answer 3

To identify which of the examples represents a discrete data constraint with viable solutions, let's review the options:

1. **Average score on a test**: This is typically continuous data because scores can take on many values (e.g., decimals). Thus, this option does not represent a discrete data constraint.

2. **Number of tests passed**: This represents discrete data because the number of tests passed can only take on whole number values (0, 1, 2, etc.). This option does represent a discrete data constraint with viable solutions.

3. **Average weight of all the newborns in a hospital ward**: This represents continuous data because weights can take on a range of values, including decimals. Thus, this option does not represent discrete data.

4. **Distance between points**: This is also continuous data, as distance is measured on a continuous scale (it can vary infinitely within a range and includes decimals). Thus, this option does not represent discrete data.

Based on this analysis, the only example that clearly represents a discrete data constraint with viable solutions is:

**Number of tests passed**.