1. What Are Quartiles?

Quartiles divide a rank-ordered dataset into four equal parts. Q1 (first quartile) is the median of the lower half, Q2 (second quartile) is the overall median, and Q3 (third quartile) is the median of the upper half of the data.

2. How Quartiles Are Calculated

The calculator uses the following method:

Steps:

1. Sort the data in ascending order
2. Find the median (Q2) of the entire dataset
3. Find the median of the lower half (Q1)
4. Find the median of the upper half (Q3)

3. Importance of Quartiles

Details: Quartiles are essential for understanding data distribution, identifying outliers, and creating box plots. They provide more robust measures of spread than range as they're less affected by extreme values.

4. Using the Calculator

Tips: Enter numeric values separated by commas. The calculator will ignore any non-numeric values. At least 3 values are recommended for meaningful quartile calculation.

5. Frequently Asked Questions (FAQ)

Q1: What's the difference between quartiles and percentiles?
A: Quartiles are specific percentiles - Q1=25th percentile, Q2=50th percentile (median), Q3=75th percentile.

Q2: How do quartiles relate to IQR?
A: Interquartile Range (IQR) = Q3 - Q1, representing the middle 50% of data.

Q3: What if my dataset has an even number of values?
A: The median (Q2) is calculated as the average of the two middle numbers. Q1 and Q3 are similarly calculated for their respective halves.

Q4: Can I calculate quartiles for categorical data?
A: No, quartiles require numerical data that can be ordered.

Q5: What's the 5-number summary?
A: Minimum, Q1, Median (Q2), Q3, Maximum - these five numbers give a complete picture of data distribution.