You can use the following formulas to find the first (Q1) and third (Q3) quartiles of a normally distributed dataset:
- Q1 = μ – (.675)σ
- Q3 = μ + (.675)σ
Recall that μ represents the population mean and σ represents the population standard deviation.
Also recall that the first quartile represents the 25th percentile of a dataset and the third quartile represents the 75th percentile of a dataset.
The following examples show how to use these formulas in practice.
Example 1: Find Quartiles Using Mean & Standard Deviation
Suppose we have a normally distributed dataset with μ = 300 and σ = 45.
We can use the following formulas to calculate the first and third quartiles of the dataset:
- Q1 = μ – (.675)σ = 300 – (.675)*45 = 269.625
- Q3 = μ + (.675)σ = 300 + (.675)*45 = 330.375
We interpret this to mean that 25% of all values in the dataset fall below 269.625 and 75% of all values in the dataset fall below 330.375.
Using these numbers, we could also calculate the interquartile range to be:
- IQR = Q3 – Q1
- IQR = 330.375 – 269.265
- IQR = 61.11
This represents the spread of the middle 50% of values in the dataset.
Example 2: Find Quartiles Using Mean & Standard Deviation
Suppose we have a normally distributed dataset with μ = 50 and σ = 2.
We can use the following formulas to calculate the first and third quartiles of the dataset:
- Q1 = μ – (.675)σ = 50 – (.675)*2 = 48.65
- Q3 = μ + (.675)σ = 50 + (.675)*2 = 51.35
We interpret this to mean that 25% of all values in the dataset fall below 48.65 and 75% of all values in the dataset fall below 51.35.
Using these numbers, we could also calculate the interquartile range to be:
- IQR = Q3 – Q1
- IQR = 51.35 – 48.65
- IQR = 2.7
This represents the spread of the middle 50% of values in the dataset.
Additional Resources
The following tutorials offer additional information about the normal distribution and quartiles:
An Introduction to the Normal Distribution
Percentile vs. Quartile vs. Quantile: What’s the Difference?
Interquartile Range vs. Standard Deviation: What’s the Difference?