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Descriptive Statistics

Computes mean, median, mode, variance, standard deviation, quartiles and outliers from pasted numbers.

Paste a column of numbers and get the summary: mean, median, mode, quartiles, standard deviation and the outliers. It shows the sample and population standard deviations side by side rather than choosing for you, because which one is right is a question about what the numbers are for.

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Numbers

Paste a column from a spreadsheet, or type them separated by commas, spaces or newlines. On this page the comma also groups digits, so 1,234 is read as one number and 1,23 as two.

Summary

count

8

sum

40

mean

5

median

4.5

min

2

max

9

range

7

mode

4

Spread

Sample (n − 1)

Use this when these numbers are a sample and you want to describe the population they came from. Excel calls it STDEV.S.

variance
4.5714
std deviation
2.1381
standard error
0.7559

Population (n)

Use this when these numbers are the whole population. Excel calls it STDEV.P.

variance
4
std deviation
2
coefficient of variation
0.4276
The two differ by 6.9% on this data. Which one is right is a question about what the numbers are for, not about the numbers, so both are shown rather than one being chosen for you.

Quartiles and outliers

Method

Q1

4

Q2 (median)

4.5

Q3

5.5

IQR

1.5

lower fence

1.75

Q1 − 1.5 × IQR

upper fence

7.75

Q3 + 1.5 × IQR

outliers

9

median abs deviation

0.5

There is no single definition of a quartile. The two methods here disagree whenever the data does not divide evenly — which is why two people can plot the same numbers and get different boxes.

Shape and intervals

95% CI of the mean

3.2122 – 6.7878

Student t = 2.365 at 7 df

skewness

0.8185

0 is symmetric

excess kurtosis

0.9406

0 is normal-tailed

geometric mean

4.6032

With 8 values the interval uses Student’s t (2.365), not the 1.96 of the normal distribution. Using 1.96 on a sample this small is the most common way a "95% interval" ends up too narrow.

Distribution

  • 2 – 3.751
  • 3.75 – 5.55
  • 5.5 – 7.251
  • 7.25 – 91

Bin count from Sturges’ rule: ⌈log₂ n⌉ + 1.

How to use it

  1. Paste the numbers

    A column out of a spreadsheet works as it is. Commas, spaces and newlines all separate, and since a comma also groups digits on an English page, its shape settles which job it is doing: 1,234 is read as one number and 1,23 as two. On the pages whose language writes the decimal with a comma — Italian, German, French, Spanish, Portuguese — that reading is the other way round, and values are separated with semicolons, the way those spreadsheets do it.

  2. Check what was ignored

    Non-numeric tokens are listed rather than silently dropped. A header row you pasted along with the data shows up there.

  3. Read the spread, not just the middle

    Mean and median together tell you about skew; the standard deviation and the coefficient of variation tell you whether the mean means anything.

Common questions

Sample or population standard deviation?

Sample, dividing by n − 1, when these numbers are a sample and you want to describe the population they came from — Excel’s STDEV.S. Population, dividing by n, when these numbers are everything there is. Both are shown along with how far apart they are on your data.

How are outliers decided?

By the 1.5 × IQR rule — anything more than one and a half interquartile ranges below the first quartile or above the third. It is a convention, not a verdict: an outlier by this rule can be a perfectly real value.

My quartiles differ from Excel’s

There are nine accepted ways to interpolate a quartile and different tools pick different ones. The difference is small and only appears with few data points. Neither is wrong; they answer slightly different questions about the same numbers.

Feed it from

Next

These accept what this tool produces, so the result can go straight in.