Complete the following statements.
In general, % of the values in a data set lie at or below the median.
% of the values in a data set lie at or below the third quartile (Q3).
If a sample consists of 600 test scores,  of them would be at or below the second quartile (Q2).
If a sample consists of 600 test scores,  of them would be at or above the first quartile (Q1).

1. In general, **50%** of the values in a data set lie at or below the median.
2. **75%** of the values in a data set lie at or below the third quartile (Q3).
3. If a sample consists of 600 test scores, **300** of them would be at or below the second quartile (Q2) (the median).
4. If a sample consists of 600 test scores, **450** of them would be at or above the first quartile (Q1).

Would you like further details or have any questions on this? 

Here are some related questions:
1. What is the interquartile range (IQR) and how is it calculated?
2. How do quartiles divide a data set, and what is their significance in box plots?
3. How does the empirical rule relate to quartiles and percentiles in normal distributions?
4. Can you explain the difference between a percentile and a quartile in statistical terms?
5. How can quartiles help in identifying outliers in a data set?

**Tip:** Quartiles are very useful for identifying the spread of data, especially when visualizing skewed distributions.

Complete the following statements.
In general, % of the values in a data set lie at or below the median.
% of the values in a data set lie at or below the third quartile (Q3).
If a sample consists of 600 test scores, of them would be at or below the second quartile (Q2).
If a sample consists of 600 test scores, of them would be at or above the first quartile (Q1).

Explore the role of quartiles and medians in dividing data sets. Learn how 50% of values lie at or below the median, and how quartiles are used to represent statistical data. Suitable for high school students learning about statistics, quartiles, and percentiles.

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