The empirical rule, also known as the 68-95-99.7 rule, states that for a bell-shaped distribution (normal distribution):

1. About 68% of the data lies within 1 standard deviation of the mean.
2. About 95% of the data lies within 2 standard deviations of the mean.
3. About 99.7% of the data lies within 3 standard deviations of the mean.

Given:

• Mean ($\mu$) = 39
• Standard deviation ($\sigma$) = 11
• Range: Between 17 and 39

Now, let's find how many standard deviations away from the mean the value of 17 is: $z = \frac{39 - 17}{11} = 2$ So, 17 is 2 standard deviations below the mean.

According to the empirical rule, about 95% of the data lies within 2 standard deviations of the mean. Since the range 17 to 39 represents half of this (from the mean to 2 standard deviations below it), the percentage of requests in this range is: $\frac{95\%}{2} = 47.5\%$

Thus, the approximate percentage is $\boxed{47.5}$.

Would you like more details, or do you have any other questions?

Here are five related questions:

1. What percentage of requests fall between 28 and 50 using the empirical rule?
2. How can the empirical rule be applied to a dataset with different mean and standard deviation?
3. What is the percentage of requests falling below 17 using the empirical rule?
4. What would the range be for 68% of the requests?
5. How does the empirical rule differ from exact probabilities in a normal distribution?

Tip: The empirical rule is most accurate for perfectly normal distributions but gives a good approximation for many real-world data sets.