Statistics Calculator — Mean, Median, SD, Free Online
Compute mean, median, mode, range, variance, standard deviation, quartiles, and percentiles for any list of numbers. Browser-only.
About Statistics Calculator
A statistics calculator computes summary statistics from a list of numbers — mean (average), median (middle value), mode (most frequent), range (max − min), variance, standard deviation, quartiles (Q1, Q2, Q3), interquartile range, and selected percentiles. The ZTools Statistics Calculator accepts any list (one number per line, comma-separated, or space-separated), runs all computations in the browser, and shows results with a small distribution chart. No upload, no signup, no row limit.
Use cases
- Quick descriptive stats for a survey. A 200-row response column. Paste, get mean / median / SD / quartiles instantly — faster than opening Excel for one column.
- Compare two datasets. Stats side by side reveal which has higher central tendency, which is more spread out. Calculator runs both and tabulates.
- Spot outliers. Values more than 1.5 × IQR beyond Q1 / Q3 are conventional outliers. Calculator flags them.
- Verify a textbook problem. Homework gives a list; you computed mean = 14.5. Calculator confirms or contradicts. Useful for self-checking.
How it works
- Paste numbers. One per line, comma-separated, or space-separated. Tool detects automatically.
- Pick population vs sample. Variance and SD differ for a population (divide by n) vs a sample (divide by n−1, Bessel's correction). Default: sample.
- Configure precision. Decimals to display (default 4). Bigger numbers get scientific notation automatically.
- Read results. Table of statistics + a small histogram showing distribution shape.
Examples
Input: [1, 2, 3, 4, 5]
Output: Mean: 3. Median: 3. Mode: none (all unique). Range: 4. Sample SD: 1.5811. Q1: 2. Q3: 4. IQR: 2.
Input: [10, 20, 20, 30, 40, 100]
Output: Mean: 36.67 (skewed by 100). Median: 25 (more representative). Mode: 20. SD: 31.85. The mean-vs-median gap signals skew.
Input: Outlier detection
Output: Q1 = 20, Q3 = 40, IQR = 20. Outlier threshold: > 70 or < −10. Value 100 flagged as outlier.
Frequently asked questions
Sample SD vs population SD?
Sample SD divides by n−1 (Bessel's correction) — gives an unbiased estimate of the population SD. Population SD divides by n — exact when you have all the data. Default is sample (more common in practice).
Mean vs median — which to report?
Mean is sensitive to outliers; median isn't. For income, house prices, response times — report median. For symmetric distributions, mean and median are similar; either works.
How is the median calculated for even count?
Average of the two middle values. For [1,2,3,4], median = (2+3)/2 = 2.5.
How is mode reported when multiple modes exist?
All values tied for highest frequency. If everything is unique, "no mode" is reported. Multimodal distributions get a list.
Privacy?
All computation in the browser. Numbers never uploaded.
Maximum list size?
Practical limit is browser memory — millions of values work fine. Quartile computation is O(n log n) (sort).
Pro tips
- When mean and median diverge significantly, the data is skewed — investigate the tail.
- Always include sample size (n) when reporting any of these stats — without n, they're hard to interpret.
- For inference (significance tests, confidence intervals), use a dedicated tool — descriptive stats only describe; they don't test hypotheses.
- Outlier detection at 1.5 × IQR is a convention, not a rule. For strict outliers, use 3 × IQR or domain-specific thresholds.
Reviewed by Ahsan Mahmood · Last updated 2026-05-06 · Part of ZTools.
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