Mean, Median and Mode: Which One to Use
"Average wage" often puzzles people: why is the published figure above what most peers earn? Because the mean is pulled by extremes while the median is not. Pick the wrong summary and the conclusion follows.
What each one tells you
- Mean: sum ÷ count. Uses all data but is sensitive to outliers.
- Median: the middle value when sorted. Robust, representing a "typical" case.
- Mode: the most frequent value. Useful for categorical or discrete data (shoe sizes, ratings).
An income example
Five monthly incomes: 4,000, 4,500, 5,000, 5,500, 50,000. Mean = 13,800, median = 5,000. The single 50,000 nearly triples the mean, while the median reflects what most people actually earn.
That is why medians are more informative for income and housing.
Spread matters too
Two datasets can share a mean but differ completely. {48,49,50,51,52} and {0,25,50,75,100} both average 50, yet the second is far more spread out. Standard deviation or range captures that.
Report "central tendency + spread", not a lone average.
Quick selection guide
- Symmetric data, no outliers → mean
- Skewed or outlier-prone (income, house prices, dwell time) → median
- Categorical or discrete → mode
- Need variability → add standard deviation or range
This article provides general information and calculation methods only. It is not medical, investment or legal advice; consult a qualified professional for your situation.