How do you find the median of an even-sized list?
Sort values, then average the two middle numbers. Example: 3,7,8,10 → median = 7.5.
Results
Mean (sum / count): 2.4000
Median (middle value): 2.0000
Mode (most frequent value): 2
Summarize a dataset with mean (average), median (middle), and mode (most frequent)—see how outliers pull the mean while median holds steady.
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Mean is the arithmetic average (sum ÷ count). Median is the middle value when data are sorted. Mode is the most frequent value. For salaries [40k, 45k, 50k, 200k], median 47.5k resists the CEO spike better than mean 83.75k.
The mean is sensitive to outliers — a single very large or small value shifts it significantly. The median is often a better central measure for skewed data (incomes, house prices, reaction times).
Results
Mean (sum / count): 2.4000
Median (middle value): 2.0000
Mode (most frequent value): 2
Three different answers to “what is typical?”—each resists distortion differently.
**Mean (x̄):** add all values, divide by how many. Sensitive to outliers—a single huge sale pulls the mean up.
**Median:** sort the list, take the center. Odd count: middle value. Even count: average of two middle values. Robust for skewed income, home prices, and reaction times.
**Mode:** most common entry. A dataset can have no mode (all unique), one mode, or multiple modes (bimodal). Useful for categorical-ish numeric data—shoe size stocked most often, survey rating peaks.
**Order of sensitivity:** mean reacts to every outlier; median tolerates a few extremes; mode ignores all but frequency structure.
After center is known, spread matters—standard deviation quantifies how far points typically sit from the mean. This page summarizes location; standard deviation calculator handles dispersion.
Paste or enter a data list—get mean, median, and mode together before analyzing spread.
Concise answers for common searches — definitions, steps, and comparisons.
Sort values, then average the two middle numbers. Example: 3,7,8,10 → median = 7.5.
Use median for skewed data with outliers—income, home prices, latency—where mean is misleading.
Mode = 3 because it appears twice, more than any other value.
Yes—bimodal when two values tie for highest frequency.
Parses numeric lists (comma, space, or newline separated), sorts for median, counts frequencies for mode, and sums for mean.
Formula
Mean μ = (Σ x_i)/n. Median: middle of sorted list. Mode: argmax frequency(x). Relationship: mean ≈ median in symmetric distributions.Comma-separated numbers—copy from spreadsheet columns if needed.
All three compute from the same list—compare how outliers shift mean vs median.
Odd n: pick middle. Even n: average two middles.
Center plus spread tells the full story—open standard deviation calculator next.
Input
2, 4, 6, 8, 10Output
Mean = 6, Median = 6, Mode = noneSymmetric—mean equals median. All values unique → no mode.
Input
10, 12, 14, 15, 200Output
Mean = 50.2, Median = 14Outlier inflates mean; median stays near the cluster.
Input
3, 7, 8, 10Output
Median = (7+8)/2 = 7.5Average the two central sorted values.
Input
5, 5, 5, 8, 9Output
Mode = 5Five appears three times—most frequent.
Input
1, 1, 2, 2, 3Output
Modes = 1 and 2Two values tie at frequency 2.
Input
72, 85, 85, 90, 91Output
Mean = 84.6, Median = 85, Mode = 85Typical reporting trio for grade distributions.
Common real-world scenarios where this tool saves time.
Ten employees plus one executive: median shows typical worker pay; mean shows payroll average—report both.
Median home price resists a few mansion sales; mean can mislead buyers in skewed markets.
Mode of shoe sales last quarter picks the size to restock heaviest.
Class scores 72, 85, 85, 90, 91 → mean 84.6, median 85, mode 85.
Step-by-step chains that connect related tools for common tasks.
| Measure | Formula idea | Outlier sensitivity | Best for |
|---|---|---|---|
| Mean | Sum ÷ n | High | Symmetric numeric data |
| Median | Middle sorted | Low | Skewed distributions |
| Mode | Most frequent | None to outliers | Categorical peaks, inventory |
| Dataset | Mean | Median | Mode |
|---|---|---|---|
| 1,2,3,4,5 | 3 | 3 | none |
| 1,2,3,4,100 | 22 | 3 | none |
| 2,2,3,3,3,4 | 2.83 | 3 | 3 |
| 10,20,20,30 | 20 | 20 | 20 |
Visual skew explains mean–median gaps instantly.
Mean of three points is less reliable than mean of three thousand.
Transparency beats hiding extremes that move the average.
σ describes spread around the mean—completes descriptive stats.
Pair median as the typical value; mention mean for total-per-person averages.
Median is not the middle number in entry order—it is middle after sorting.
All unique values → no mode. Uniform frequency → no single mode.
Midrange (min+max)/2 differs from median except in symmetric cases.
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Undefined—division by zero. Enter at least one value.
Yes if values repeat exactly. Continuous measurements rarely repeat—mode is less useful then.
Trimmed mean drops extremes before averaging—between mean and median robustness. Not computed here.
Skewness and outliers pull the mean toward the long tail; median stays at the 50th percentile.
Standard deviation or variance for spread; quartiles for box plots.
Odd n: yes. Even n: median may be the average of two middle points—not necessarily in the list.
Weighted mean = Σ(weight × score)/Σ(weights)—extends arithmetic mean; enter expanded data or compute manually.
Dataset values stay in your browser for local statistics.
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Reviewed by EverydayTools Editorial Team on 2026-07-03.
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