Enter numbers to calculate comprehensive statistics including mean, median, variance, quartiles, and more.
Mean (Average)
18.00
Count6
Sum108.00
Minimum4.00
Maximum42.00
Range38.00
Median15.50
Mode4.00
Variance (Sample)182.00
Std Dev (Sample)13.49
Q1 (25th percentile)9.75
Q3 (75th percentile)21.25
IQR11.50
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What is the Statistics Calculator?
Statistics describes and summarizes data. Key metrics include mean (average), median (middle value), mode (most frequent), range (spread), variance (spread squared), standard deviation (typical deviation from mean), and quartiles (values that divide data into quarters). These measures help you understand distribution, find outliers, and make data-driven decisions.
How it works
Enter numbers separated by commas, spaces, or line breaks. The calculator sorts the data, counts values, computes sums, and calculates all statistical measures. It automatically handles decimals, negative numbers, and datasets of any size. Results update live as you type.
Mean is the sum divided by count. Variance measures spread from the mean (using sample formula n−1). Standard deviation is the square root of variance. Quartiles divide sorted data into four equal parts; IQR is the range of the middle 50% of data.
Examples
Input
Result
Notes
4, 8, 15, 16, 23, 42
Mean: 18.00; Median: 15.50; Std Dev: 14.28
Six numbers: mean is (4+8+15+16+23+42)÷6 = 18; median is the average of 15 and 16; standard deviation shows how spread out the values are
85, 90, 78, 92, 88
Mean: 86.60; Variance: 31.30; Range: 14
Five test scores: variance is 31.30, range is 92−78 = 14, showing moderate spread in performance
10, 10, 20, 20, 20, 30
Mean: 18.33; Mode: 20; IQR: 10
Mode (20) appears most often; IQR (10) is the range of the middle 50% of values
How to use the Statistics Calculator
Enter all your numbers into the textarea (comma-separated, space-separated, or each on a new line)
The calculator automatically computes all statistics as you type
Read the mean in the large result box, then see all other measures in the stats grid below
Use the metrics to understand your data: mean for typical value, median for middle, std dev for spread, quartiles for distribution shape
Copy results or clear to analyze a new dataset
Benefits
Instant calculation — all 13 statistics computed live without clicking a button
Handles unlimited data — process 10 values or 10,000 with equal ease
Sample formulas — uses n−1 variance and std dev for accurate sample statistics
Quartile analysis — visualize data distribution with Q1, Q3, and IQR
Reduces human error — no arithmetic mistakes; no manual sorting for median or quartiles
Free and private — all computation happens in your browser; no data sent to servers
Tips & common mistakes
Common mistakes
Mixing population and sample formulas — this calculator uses sample variance (n−1) appropriate for subsets; use n for entire populations
Misinterpreting median vs mean — median is the middle value when sorted; mean is the sum divided by count; median is robust to outliers
Forgetting to include all data — ensure your list is complete before calculating; missing values skew results
Confusing std dev with variance — variance is squared deviation units; std dev is in the same units as your data (more intuitive)
Tips
Paste from a spreadsheet directly — most calculators handle comma, space, or tab-separated values
Use the median and IQR to spot outliers — values far outside the quartile range may be data entry errors
Standard deviation tells you spread in practical terms — about 68% of data falls within ±1 std dev of the mean (normal distribution)
For large datasets, round results to 2–3 decimal places unless precision is critical
Frequently asked questions
What's the difference between variance and standard deviation?
Variance is the average squared deviation from the mean. Standard deviation is the square root of variance, so it's in the same units as your data. Both measure spread, but std dev is more interpretable.
Why does the calculator use n−1 for variance and standard deviation?
This calculator uses the sample variance formula (dividing by n−1 instead of n). Use this when analyzing a subset of data. For a complete population, divide by n instead.
What are Q1, Q3, and IQR?
Q1 is the 25th percentile (the value below which 25% of data falls). Q3 is the 75th percentile. IQR (interquartile range) is Q3−Q1, representing the spread of the middle 50% of data.
Can I use negative numbers?
Yes. Negative numbers are treated normally. Mean, median, variance, and all other metrics handle negative values correctly.
What if all my numbers are the same?
The mean and median equal that number. Variance and std dev are zero. Q1, Q3, and IQR are also zero because there's no spread.
How many numbers do I need?
At least one. For meaningful variance and std dev, use at least 2–3 values. The larger your dataset, the more reliable the statistics.