Mean Absolute Deviation
Understanding Mean Absolute Deviation (MAD)
In statistics, Mean Absolute Deviation (MAD) is a way to measure how spread out or scattered a set of data is. It tells us the average distance between each data point and the mean of the data set.
A larger MAD means the data points are far away from the mean (more spread out). A smaller MAD means the data points are clustered closely around the mean (less spread out).
How to Calculate MAD
Finding the MAD takes three simple steps:
- Find the mean (average) of the data set.
- Find the distance of each data point from the mean. This is the absolute value of the difference: ∣data point−mean∣.
- Find the mean of those distances by adding them all up and dividing by the number of data points.
Example Problems
Example 1: Find the MAD of 2, 4, 6, 8, 10
Step 1: Find the mean. Mean=52+4+6+8+10=530=6
Step 2: Find the distance of each point from the mean (6).
- ∣2−6∣=4
- ∣4−6∣=2
- ∣6−6∣=0
- ∣8−6∣=2
- ∣10−6∣=4
Step 3: Find the mean of these distances. MAD=54+2+0+2+4=512=2.4
The Mean Absolute Deviation is 2.4.
Example 2: Calculate the MAD for 10, 12, 8, 15, 5
Step 1: Find the mean. Mean=510+12+8+15+5=550=10
Step 2: Find the distances from the mean (10).
- ∣10−10∣=0
- ∣12−10∣=2
- ∣8−10∣=2
- ∣15−10∣=5
- ∣5−10∣=5
Step 3: Average the distances. MAD=50+2+2+5+5=514=2.8
The Mean Absolute Deviation is 2.8.
Interpreting MAD
Question: Dataset A has a MAD of 1.5 and Dataset B has a MAD of 4.2. Which is more spread out?
Answer: Dataset B is more spread out. Because the MAD represents the average distance from the mean, a higher number (4.2>1.5) indicates that the values in Dataset B are scattered further away from their average compared to Dataset A.