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To solve the problem:

1. **Identify the percentiles for the given z-scores**:
   - From the table, the percentile for \( z = 1.3 \) is \( 90.32\% \).
   - The percentile for \( z = 2.1 \) is \( 98.21\% \).

2. **Subtract the smaller percentile from the larger percentile**:
   - \( 98.21\% - 90.32\% = 7.89\% \).

### Answer:
The percentage of data items in the normal distribution that lie between \( z = 1.3 \) and \( z = 2.1 \) is **7.89%**.

Would you like me to explain this further? Here are some related questions for deeper understanding:

1. What is the purpose of z-scores in a normal distribution?
2. How are percentile values interpreted in a z-table?
3. Why does subtracting the percentiles give the percentage of data between two z-scores?
4. Can this method be applied to any normal distribution, or are there exceptions?
5. How can this process be automated using statistical software?

### Tip:
Always ensure that the z-scores are listed in increasing order to avoid subtracting in the wrong direction.

Use the table below to find the percentage of data items in a normal distribution that lie between z = 1.3 and z = 2.1.

Learn how to calculate the percentage of data in a normal distribution between z-scores 1.3 and 2.1 using percentile values from a z-table. Includes step-by-step guidance on subtracting percentile values.

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