Let’s tackle the problem. We know the formula for <span>the height of the ball is as follows:
</span>

<span>
Here, x represents </span><span>the horizontal distance in yards that the ball has traveled in the air. Given that distance is always a positive value, we conclude that x must be greater than or equal to 0. Thus:
</span>

<span>
The horizontal plane indicates the function's zero point, and since the ball cannot have negative height values,

must also remain positive. Ultimately, the graph reveals that the suitable domain is:
</span>

<span>
</span><span>
</span>
Response:
The more trials conducted, the stronger the observed theoretical trend becomes
Stepwise explanation:
Firstly, we need to define the probabilities,
-Theoretical probability quantifies success versus total possible outcomes of an experiment.
-Experimental probability calculates the ratio of the desired outcome relative to the total attempts made in the experiment.
Accordingly, the reasoning that best supports this is that as the experiment is repeated, the experimental probability aligns more closely with the theoretical probability, because repetition increases the likelihood of achieving predicted results.
Response:
This is the C=intercept of the regression line
Step-by-step clarification:
The regression line's slope is logically interpreted as the average increase in collar size for each 1cm increment in height.