Mean vs Median
These terms are close enough that students often swap them in conversation, but statistics does not let you swap them in an argument. Each one answers a different question about data, evidence, or study design.
Read the side-by-side breakdown below with one goal in mind: identify what kind of claim each idea supports and what goes wrong when that claim is stretched too far.
Mean (Average)
The sum of all values divided by the number of values
Strengths
- ✓ Easy to calculate
- ✓ Uses all data points
- ✓ Good for symmetric distributions
Weaknesses
- ✗ Affected by outliers
- ✗ Can be misleading with skewed data
Median
The middle value when data is ordered
Strengths
- ✓ Not affected by outliers
- ✓ Good for skewed data
- ✓ Represents the "typical" value
Weaknesses
- ✗ Ignores extreme values
- ✗ Less mathematically useful
Key Takeaway
Use mean for symmetric data without outliers. Use median when you have skewed data or outliers that could distort the average.
Quick Self-Check
- What question am I answering about the data?
- What kind of conclusion would be too strong for this idea?
- Which choice would change how I interpret the same dataset?