Dataset summary

Dataset
10 values · population
Try one

Mean

10.7

Sum divided by count

Median

9

Middle value when sorted

Mode

8

Most frequent value

Distribution321
Q1 7.25Q3 14.25
Count10
Unique values9
Sum107
Minimum3
Maximum21
Range18
Population variance30.01
Population std deviation5.4781
Mean absolute deviation4.64
Interquartile range7
Geometric mean9.2473
Harmonic mean7.8164
Valuesas entered
127538101518218
Values10
Mean10.7
Median9
Std deviation5.4781

Average & Median Calculator

Paste a dataset and see its centre, spread, quartiles, outliers, and less familiar averages in one readable summary. Choose sample or population statistics, control the precision, and keep the original values in your browser.

Statistics in one pass
12
Outlier rule
1.5× IQR
Sample variance basis
n − 1
Values uploaded
0

Step by step

How to use it

  1. 01

    01Paste the values

    Use commas, spaces, or new lines. Invalid fragments are skipped and called out instead of corrupting the result.

  2. 02

    02Choose the right basis

    Use population when the list is the whole group; use sample when it stands in for a larger group.

  3. 03

    03Compare centre and spread

    Read mean beside median, then use standard deviation, quartiles, and the histogram to see what the headline average hides.

  4. 04

    04Copy the summary

    Set the useful precision and copy a compact report for notes, homework, or analysis.

Worked example

A salary-shaped dataset

One large value pulls the mean farther than the median.

Given

Values
18, 20, 21, 22, 24, 75
Basis
Population

Centre and spread

mean     30
median   21.5
range    57
Q1       20
Q3       24
IQR      4
Typical centre
median 21.5
Upper fence
30
Potential outlier
75

The mean is mathematically correct, but the median better describes the cluster because 75 pulls the mean upward.

Why this one

How to read a dataset honestly

Mean and median answer different questions

The mean shares the total equally; the median finds the middle observation. Skew and outliers separate them.

Sample variance needs n − 1

A sample tends to understate the spread of its parent population. Bessel's correction compensates for that bias.

Outlier does not mean error

The 1.5 × IQR rule flags unusually distant observations. A flagged value may be the most important fact in the data.

Geometric and harmonic means have jobs

Use the geometric mean for multiplicative growth and the harmonic mean for rates over equal distances—not as replacements for every average.

The judgement call

Which average should you report?

  • Roughly symmetric measurements

    Mean

    Every observation contributes and no long tail dominates.

  • Income, house prices, or a skewed distribution

    Median

    The middle resists a few extreme values.

  • Compound returns or growth factors

    Geometric mean

    The changes multiply from period to period.

  • Average speed over equal distances

    Harmonic mean

    Time is inversely proportional to the rate.

Reference

Statistics used here

Median
Middle sorted valueFor an even count, the two middle values are averaged.
Population variance
Σ(x − μ)² / n
Sample variance
Σ(x − x̄)² / (n − 1)
Outlier fences
Q1 − 1.5 IQR · Q3 + 1.5 IQR

FAQ

Questions, answered plainly

What is the difference between average and median?

Average usually means arithmetic mean: add the values and divide by their count. Median is the middle value after sorting, so it is less affected by extremes.

Should I use sample or population standard deviation?

Use population when your list contains every member you mean to describe. Use sample when those observations estimate a larger population.

How are quartiles and outliers calculated?

The calculator splits the ordered data around its median, finds Q1 and Q3, then flags values below Q1 − 1.5 × IQR or above Q3 + 1.5 × IQR.

Can I paste values from a spreadsheet?

Yes. Commas, spaces, tabs, and line breaks all work, so a copied column or row can be pasted directly.

Are my numbers uploaded?

No. Parsing and every statistic run locally in your browser.

Your dataset is parsed and analysed entirely in the browser. Nothing is uploaded or retained.