To interpret the given slope of 12 for the line of best fit in the context of the data, we need to understand what the slope represents.
In this case, the slope of 12 means that for every additional hitting attempt, Ava averages an increase of 12 kills. This indicates a relationship where, on average, for each hitting attempt, her success rate (in terms of kills) increases.
Now let's evaluate the provided statements:
-
Ava’s number of kills increases by 2 for every game. - This is not correct, as the slope does not indicate that kills increase by 2 for each game; it refers to the number of hitting attempts.
-
Ava has about 2 kills for every hitting attempt. - This is also not correct, as it does not match the slope interpretation.
-
Ava has about 1 kill for every 2 hitting attempts. - This might seem plausible, but it doesn't accurately represent the slope of 12.
-
Ava has about 2 kills for every game. - Again, this is incorrect regarding the context of the slope.
Given the options, none of the statements accurately reflect the interpretation of the slope of 12. The slope should indicate the rate of increase in kills per hitting attempt or a more precise interpretation in terms of scores given the data.
However, if we consider the average representation that might closely relate to the scaling, the answer can be more nuanced than any of the statements provided.
In conclusion, based on the slope provided (12), which usually means an increase in kills relative to increases in attempts, none of the options truly capture the essence, but the closest implication is related to performance rate (kills to attempts). If forced to select from the existing statements, one might argue for revising how they understand "kills per attempt" vs "attempts leading to increases," therefore check reevaluating any further context with empirical data or guidance on what's measured (kills per attempts). As the question stands, though, there seems to be a mismatch.
Overall, keep an eye on typical relationships; with kills ~= large attempts, but assessment would need to reunderstand adjacent figures or linear fitting for best application.