Calculate Quartile Deviation & Semi-IQR

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Calculation Results

Primary Metric Output --
Metric Breakdown 1--
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Mathematical Standard--

Calculated using semi-interquartile dispersion equations: \text{QD} = \frac{Q_3 - Q_1}{2}, \quad \text{Coeff of QD} = \frac{Q_3 - Q_1}{Q_3 + Q_1}

*Note: Quartile deviation measures absolute half-spread of the central 50% of data, robust against extreme outliers.

Quick Summary

The Quartile Deviation Calculator evaluates Semi-Interquartile Range ($\text{QD} = \frac{Q_3 - Q_1}{2}$), Coefficient of Quartile Deviation, $Q_1$, $Q_3$, and Interquartile Range (IQR).

Formula Explanation

\text{Quartile Deviation QD} = \frac{Q_3 - Q_1}{2}
\text{Coefficient of QD} = \frac{Q_3 - Q_1}{Q_3 + Q_1}

How It Works

Quartile deviation (also called semi-interquartile range) is half the distance between the 75th percentile ($Q_3$) and 25th percentile ($Q_1$). The Quartile Deviation Calculator sorts your dataset, computes quartiles, and calculates absolute and relative quartile deviation metrics.

Step-by-Step Worked Example

Practical Problem: Calculate quartile deviation for dataset: 10, 15, 20, 25, 30, 35, 40, 45 ($n = 8$).

  1. Step 1: Calculate $Q_1$ (25th percentile): $Q_1 = \mathbf{16.2500}$.
  2. Step 2: Calculate $Q_3$ (75th percentile): $Q_3 = \mathbf{38.7500}$.
  3. Step 3: Calculate Interquartile Range ($\text{IQR}$): $38.75 - 16.25 = \mathbf{22.5000}$.
  4. Step 4: Divide IQR by 2 for Quartile Deviation ($\text{QD}$): $22.50 / 2 = \mathbf{11.2500\text{ Quartile Deviation}}$.
  5. Step 5: Calculate Coefficient of QD: $(38.75 - 16.25) / (38.75 + 16.25) = 22.50 / 55.00 = \mathbf{0.4091}$.

Real-World Calculation Examples

Scenario 1: 8-Item Dataset (10 to 45)

Parameters: n = 8
Result: Quartile Deviation 11.2500 (IQR 22.5000).

Scenario 2: Skewed Salary Data (Q1 $40k, Q3 $100k)

Parameters: Q1 $40k, Q3 $100k
Result: QD $30,000 (Semi-IQR spread).

Scenario 3: Symmetrical Test Scores (Q1 70, Q3 90)

Parameters: Q1 70, Q3 90
Result: QD 10.00 points (IQR 20.00 points).

Scenario 4: Coefficient of QD Relative Comparison

Parameters: Q1 15, Q3 45
Result: Coeff of QD 0.5000.

Key Benefits of Using This Calculator

Outlier Resistant Dispersion

Provides a measure of dispersion unaffected by extreme tail values.

Coefficient of Quartile Deviation

Computes relative dimensionless quartile deviation for comparing datasets.

Full Quartile Summary

Displays $Q_1$, $Q_2$ (Median), $Q_3$, and IQR.

100% Free & Client-Side

Executes locally in your browser with zero latency or web server transmission.

Frequently Asked Questions (FAQ)

What is quartile deviation?

Quartile deviation (semi-interquartile range) is half the difference between the third and first quartiles ($\text{QD} = \frac{Q_3 - Q_1}{2}$).

Why use quartile deviation instead of standard deviation?

Quartile deviation is preferred for skewed distributions with extreme outliers because it depends strictly on the middle 50% of data.

What is Coefficient of Quartile Deviation?

Coefficient of QD is $\frac{Q_3 - Q_1}{Q_3 + Q_1}$, a relative dimensionless measure of quartile dispersion.

What is relationship between QD and IQR?

Quartile deviation is exactly half of the Interquartile Range ($\text{QD} = \text{IQR} / 2$).

In a normal distribution, how does QD relate to standard deviation ($\sigma$)?

For a normal bell curve, $\text{QD} \approx 0.6745 \cdot \sigma$.

Can quartile deviation be zero?

Yes — if $Q_3 = Q_1$ (e.g. more than 50% of data points are identical), $\text{QD} = 0$.

Can quartile deviation be negative?

No — since $Q_3 \ge Q_1$, quartile deviation is always non-negative ($\ge 0$).

What is mean deviation vs quartile deviation?

Mean deviation averages absolute deviations from the mean; quartile deviation measures half-spread between $Q_3$ and $Q_1$.

How do I calculate QD in Excel?

Use formula =(QUARTILE(range, 3) - QUARTILE(range, 1)) / 2.

When is QD best utilized in data analysis?

QD is best used when data is open-ended at extremes or when median is reported as central tendency.