Mean vs Median
Both the mean and the median measure the center of a dataset, but they behave differently when data contains extreme values.
In short: The mean is the average of all values.
The median is the middle value of an ordered dataset.
When outliers exist, the median is often more reliable.
Key Difference
The mean uses every value in the dataset. The median depends only on position.
Because of this, the mean is sensitive to extreme values, while the median is not.
Example Without Outliers
Dataset: 2, 4, 6, 8, 10
Mean = 6
Median = 6
When data is symmetric, both measures are often equal.
Example With an Outlier
Dataset: 1, 2, 3, 4, 100
Mean = 22
Median = 3
The extreme value heavily influences the mean,
but the median still reflects the typical observation.
When to Use Mean or Median
Use the mean when data is balanced and without extreme values.
Use the median when data is skewed or contains outliers.
In many cases, comparing both provides the clearest understanding.
FAQ – Mean vs Median
Is the mean always higher than the median?
No. It depends on the distribution of the data.
Which is better?
Neither is universally better. It depends on the dataset.
Should I report both?
Yes. Reporting both often gives a clearer picture.