The question in the image is asking what percentage of the area under the standard normal distribution curve lies between $z = -2.499$ and $z = 2.499$.

This can be answered by finding the cumulative probability associated with these $z$-scores. The standard normal distribution table (or using statistical software) can give us the cumulative probabilities for these $z$-values.

1. For $z = 2.499$, the cumulative probability is approximately 0.9937.
2. For $z = -2.499$, the cumulative probability is approximately 0.0063.

To find the percentage of the area between these two points, subtract the smaller cumulative probability from the larger one:

$0.9937 - 0.0063 = 0.9874$

Thus, about 98.74% of the area under the curve lies between $z = -2.499$ and $z = 2.499$.

You should enter 98.74% in the answer box.

Would you like more details on how this calculation works? Let me know if you have any questions.

Here are five related questions you might consider:

1. What does a standard normal distribution represent?
2. How do you use the z-table to find cumulative probabilities?
3. What does the area under the curve between two z-values represent in practical terms?
4. How does changing the z-scores affect the area under the curve?
5. What is the significance of 68-95-99.7 rule in normal distributions?

Tip: Always remember that the area under a normal distribution curve represents probabilities, and the total area under the curve equals 1, or 100%.