https://file.aiquickdraw.com/mathbot/file/1727741915955xifpqzfk.jpg

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.

The image shows two graphs of standard normal distributions. One graph has z-scores -0.84 and 1.28, while the second graph shows an area under the curve with a value of 0.8907.

Explore standard normal distribution graphs with z-scores of -0.84 and 1.28, and calculate the area under the curve corresponding to a probability of 0.8907. Learn about z-scores, their significance, and how to use them in probability calculations. Suitable for students in Grades 9-12.

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