This is a box plot accompanied by a series of questions asking about the percentage of data values within certain ranges. Let's analyze the box plot first:

• The minimum value is 8, and the maximum value is 20.
• The quartiles (from the plot):
  • The first quartile (Q1) is at approximately 11.
  • The median (Q2) is at approximately 14.5.
  • The third quartile (Q3) is at approximately 17.

Question Breakdown:

1. What percentage of the data is between 8 and 9?

   • Since the minimum starts at 8 and the box plot suggests that this range covers the whisker before the first quartile, this would represent a very small portion of the data, typically 0%–25%. However, since 9 is far from the first quartile, this is closer to 0%.

2. What percentage of the data is between 9 and 17?

   • The range from 9 to 17 covers all values from the first quartile (Q1) to the third quartile (Q3). This represents 50% of the data.

3. What percentage of the data is between 17 and 18?

   • The range between 17 (the third quartile) and 18 covers part of the whisker leading to the maximum, representing 25% of the data, but only a fraction of this portion is between 17 and 18, likely around 12.5%.

4. What percentage of the data is between 18 and 20?

   • The range from 18 to 20 covers the last segment of the whisker leading up to the maximum. This would also cover around 12.5% of the data.

Filled Out:

• 0% of the data values are between 8 and 9.
• 50% of the data values are between 9 and 17.
• 12.5% of the data values are between 17 and 18.
• 12.5% of the data values are between 18 and 20.

Let me know if you need further clarification!

Here are 5 related questions:

1. What does the interquartile range (IQR) tell us about the spread of the middle 50% of the data?
2. How does a box plot help in identifying outliers?
3. How would you calculate the mean from a box plot?
4. What is the significance of the whiskers in a box plot?
5. How can a box plot help in comparing two different datasets?

Tip: The interquartile range (IQR) can be used to identify potential outliers using the formula: $[Q1 - 1.5 \times IQR, Q3 + 1.5 \times IQR]$.