Analyze grouped distributions with quartile deviation and quartiles. Check cumulative frequency steps before final interpretation. Download organized outputs for reports, classes, or audits today.
Enter class intervals and their frequencies. Use the buttons to add rows, remove rows, or load the example data.
| Class Interval | Frequency |
|---|---|
| 10 - 20 | 4 |
| 20 - 30 | 6 |
| 30 - 40 | 10 |
| 40 - 50 | 14 |
| 50 - 60 | 8 |
| 60 - 70 | 4 |
Q1 = L + ((N/4 - cf) / f) × h
Q3 = L + ((3N/4 - cf) / f) × h
Quartile Deviation = (Q3 - Q1) / 2
Coefficient of Quartile Deviation = (Q3 - Q1) / (Q3 + Q1)
Here, L is the lower boundary of the quartile class, N is total frequency, cf is cumulative frequency before the quartile class, f is the quartile class frequency, and h is class width.
Step 1: Choose the correct interval type.
Step 2: Enter each class interval in order.
Step 3: Enter the matching frequency for every class.
Step 4: Click the calculate button.
Step 5: Read the result box above the form.
Step 6: Review Q1, Q3, the interquartile range, and quartile deviation.
Step 7: Export the summary and calculation table to CSV or PDF when needed.
A grouped data quartile deviation calculator helps measure spread in a frequency distribution. It focuses on the middle half of the data. That makes it useful when extreme values may distort the full range. In statistics, quartile deviation is also called the semi interquartile range. It is a practical dispersion measure for class intervals, cumulative frequency tables, and summarized datasets.
This calculator estimates Q1 and Q3 from grouped observations. It then calculates the interquartile range and quartile deviation. You can also review the cumulative frequency before each class. That helps you verify the quartile class selection. The tool is useful for classroom work, test preparation, research notes, and business reporting where grouped statistical data must be interpreted quickly.
The method uses the standard grouped data quartile formula. First, the total frequency is found. Next, the calculator locates the N/4 and 3N/4 positions. Then it identifies the correct quartile classes. After that, it applies interpolation within those classes. This process gives smoother estimates than simply picking a class label. It works well for continuous intervals and also for inclusive integer intervals.
Use this grouped data quartile deviation calculator when raw observations are not available. Many reports show class intervals with frequencies only. In that case, quartile deviation gives a clear picture of variability around the center. A smaller value suggests tighter clustering. A larger value suggests wider spread. Because the result is based on quartiles, it is often more stable than range based measures.
Quartile deviation measures the spread of the middle 50 percent of a dataset. It is half of the interquartile range and reduces the effect of extreme values.
Yes. Both names describe the same measure. The value is calculated as (Q3 minus Q1) divided by 2.
Use grouped data formulas when your data is summarized into class intervals and frequencies. They help estimate quartiles when raw observations are unavailable.
Interval type matters because inclusive integer classes need boundary adjustment. Continuous or exclusive classes already behave like boundaries.
The interquartile range is Q3 minus Q1. Quartile deviation is half of that value. Both describe spread, but quartile deviation is the smaller summary measure.
Yes. The calculator uses the width of the identified quartile class during interpolation. Just enter the intervals in the correct order.
The calculator accepts decimal frequencies. However, most grouped frequency tables use whole numbers, so double check your source data before interpreting the result.
A smaller quartile deviation means the central half of the data is more tightly packed. A larger value means greater spread around the median area.
Important Note: All the Calculators listed in this site are for educational purpose only and we do not guarentee the accuracy of results. Please do consult with other sources as well.