Statistics Calculator

Statistics calculator

Paste a dataset as comma-, space-, semicolon-, or newline-separated values. This calculator parses the numbers in your browser and returns descriptive statistics without uploading the dataset.

Measures returned

Category	Measures	What it shows
Count and total	Count, sum	Dataset size and combined value
Central tendency	Mean, median, mode	Typical or most frequent values
Minimum and maximum	Minimum, maximum, range	Overall limits and their difference
Quartiles	Q1, Q2, Q3, IQR	Distribution across four sections
Dispersion	Population/sample variance and standard deviation	How far values spread from the mean

How calculations work

The mean divides the sum by the number of values. The median is the middle value after sorting; for an even-sized dataset, it is the average of the two middle values. A mode is a value with the highest frequency. If every value occurs once, the dataset has no mode.

Quartiles use linear interpolation on sorted values. Q1 is the 25th percentile, Q2 is the median, and Q3 is the 75th percentile. The interquartile range (IQR) is Q3 − Q1, so it describes the middle half of the dataset while reducing the effect of extreme outliers.

Population variance divides the sum of squared deviations by N. Sample variance divides by N − 1 to estimate the spread of a larger population from a sample. Standard deviation is the square root of variance and uses the same population or sample convention.

Common uses

• Check exam scores, survey responses, or experiment measurements.
• Compare average performance with median performance when outliers exist.
• Identify unusually wide or narrow distributions with range and IQR.
• Report sample standard deviation in research or quality-control work.
• Validate a manually collected dataset before importing it into a spreadsheet.

Example input

12, 15, 15, 18, 20

For this dataset, the calculator finds a mean of 16, a median of 15, a mode of 15, and a range of 8. Values can also be entered as:

12
15
15
18
20

Equivalent calculations in code

JavaScript:

const values = [12, 15, 15, 18, 20];
const mean = values.reduce((sum, value) => sum + value, 0) / values.length;

Python:

from statistics import mean, median, multimode

values = [12, 15, 15, 18, 20]
print(mean(values), median(values), multimode(values))

SQL:

SELECT
  COUNT(*) AS count,
  SUM(value) AS total,
  AVG(value) AS mean,
  MIN(value) AS minimum,
  MAX(value) AS maximum
FROM measurements;

Interpreting results

Use the mean when every value should contribute equally. Use the median when outliers or skewed values could distort the average. Compare population and sample measures based on how the data was collected, not on which result is larger. A low standard deviation means values cluster near the mean; a high standard deviation means they are more dispersed.