Overview
Mean and median are both measures of central tendency, but they respond very differently to outliers and skewed data. The mean (average) adds all values and divides by the count. The median finds the exact middle value when data is sorted.
The Mean Calculator computes the arithmetic average of your dataset. The Median Calculator finds the middle value, which is more resistant to extreme outliers.
Key Differences
**Calculation:** Mean sums all values and divides by the count. Median sorts all values and picks the middle one.
**Sensitivity to outliers:** Mean is heavily influenced by extreme values. Median is resistant to outliers.
**Skewed data:** In right-skewed data (like income), the mean is pulled higher than the median. In symmetric data (like height), they are approximately equal.
**When they differ:** A large gap between mean and median signals skewed data or significant outliers.
**Common use:** Mean is standard in science and statistics. Median is preferred for income, home prices, and other skewed distributions.
When to Use the Mean Calculator
- Your data is roughly symmetric without extreme outliers - You need to calculate grade point averages, batting averages, or test scores - You are working with measurements that follow a normal distribution (height, temperature) - You need to compute totals from averages (mean x count = total) - You are doing further statistical calculations that require the arithmetic mean
When to Use the Median Calculator
- Your data contains extreme outliers that would skew the average - You are looking at income, home prices, or wealth data - You want to know what the "typical" value is in a skewed dataset - You are comparing groups where outliers could distort the mean - You want a measure of center that is not affected by a few extreme values
Frequently Asked Questions
Q: Why is median household income used instead of mean? A: Because a few extremely high incomes pull the mean up significantly, making it unrepresentative. The median better represents what a typical household earns.
Q: When are mean and median the same? A: In perfectly symmetric distributions (like a normal bell curve), the mean and median are equal. They diverge as data becomes more skewed.
Q: Can I use both together? A: Yes. Comparing the two reveals the shape of your data. If mean is much higher than median, the data is right-skewed. If they are close, the data is roughly symmetric.
Q: Is one always better than the other? A: No. Each serves a different purpose. The mean is better for symmetric data and when you need mathematical properties. The median is better for skewed data or when outliers are present.
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