The image you provided shows two graphs of standard normal distributions. Let's break them down:

1. Graph 11:

   • The curve represents a standard normal distribution with a mean of 0 and a standard deviation of 1.
   • Two z-scores are marked: $z = -0.84$ and $z = 1.28$, defining a region between these values.
   • This region, shaded in green, likely represents the area under the curve between these z-scores, which corresponds to the probability or percentage of data that falls within this range.

2. Graph 13:

   • The curve again represents a standard normal distribution.
   • The area shaded corresponds to the region from $z = 0$ up to an unknown positive value of $z$.
   • The area under the curve for this region is given as 0.8907. This means that 89.07% of the data lies between 0 and the unknown $z$-score.

Would you like further explanation on how to calculate the areas under the curve or z-scores? Let me know if you'd like to dive deeper into these concepts.

Here are five related questions to consider:

1. How do you calculate the area under a standard normal curve between two z-scores?
2. What is the significance of z-scores in a standard normal distribution?
3. How do you use a z-table to find the area under the normal curve?
4. What does a negative z-score represent in the context of a standard normal distribution?
5. How would you calculate the unknown z-score corresponding to an area of 0.8907?

Tip: In a standard normal distribution, the total area under the curve always equals 1 (or 100%), so areas represent probabilities.