SOLVETUTORMATH SOLVER

Instrument MI-07-001 · Statistics

Descriptive Statistics Calculator

Paste your numbers; the instrument returns the centre, the spread, and the quartiles — and shows the arithmetic it used to get there.

Instrument MI-07-001
Sheet 1 OF 1
Rev A
Verified
Type 07 — Descriptive Statistics SER. 2026-07001

Mean (x̄)

5.0000

x̄ = Σx ⁄ n

4.5000 Median
2.1381 Std. deviation (sample)
2.0000 Std. deviation (population)
8 Count (n)
2.0000 Minimum
9.0000 Maximum
4.0000 Q1 (25th percentile)
5.5000 Q3 (75th percentile)
1.5000 IQR
The working Every figure verified twice
  1. x̄ = 40.0000 ⁄ 8 = 5.0000
  2. s = √(32.0000 ⁄ 7) = 2.1381
Worksheet log
  1. No entries yet — change an input to log a scenario.

How this instrument works

Before any serious analysis, you describe: where is the data centred, and how far does it wander? The mean and median answer the first question two different ways — the mean is the balance point, the median the middle value. When they disagree noticeably, your data is skewed, and that disagreement is itself a finding.

The standard deviation answers the second question, and it comes in two flavours this instrument reports separately: the population form (divide by n) when your numbers are the whole story, and the sample form (divide by n−1) when they are a sample standing in for something larger. Textbooks fight about this; your data does not — it just needs you to know which one you are quoting.

Everything runs in your browser as you type. The data never leaves the page — paste exam scores, revenue figures or lab measurements without them touching any server.

xˉ=xn\bar{x} = \frac{\sum x}{n}s=(xxˉ)2n1s = \sqrt{\frac{\sum (x - \bar{x})^{2}}{n-1}}σ=(xxˉ)2n\sigma = \sqrt{\frac{\sum (x - \bar{x})^{2}}{n}}
x̄ — mean · s — sample standard deviation · σ — population standard deviation · quartiles by linear interpolation between closest ranks (the spreadsheet convention).
  • Paste or type your numbers — commas, spaces or new lines all work as separators.
  • Read the headline mean; median, deviations, quartiles and extremes line up beneath it.
  • Check the working block for the substitution — Σx, n, and the squared-deviation sum are all shown.

Worked example — the eight quiz scores

The default data set {2, 4, 4, 4, 5, 5, 7, 9} is the classic teaching example. Sum is 40 over n = 8, so the mean is exactly 5. Sort the list and the middle two values are 4 and 5, so the median is 4.5 — a touch below the mean, because the 9 drags the balance point right.

The squared deviations sum to 32. Population σ = √(32 ⁄ 8) = exactly 2; sample s = √(32 ⁄ 7) ≈ 2.14. Same data, two honest answers — the difference is only about whether these eight scores are the whole class or a sample of a bigger one.

Questions

Sample or population standard deviation — which one do I quote?

Ask whether your numbers are everything (all 8 quiz scores that exist → population, σ) or a sample standing in for more (8 customers out of thousands → sample, s). The sample form divides by n−1 to correct the bias of estimating the mean from the same data. When in doubt, quote the sample form — it is the conservative choice.

Why do my quartiles differ from my textbook's?

There are at least nine published quartile conventions. This instrument uses linear interpolation between closest ranks — the same method as the standard spreadsheet PERCENTILE function — so Q1 of the default set is 4, not the 3.5 some textbook methods give. Neither is wrong; they are different definitions, and this sheet states which one it uses.

When is the median better than the mean?

Whenever a few extreme values would mislead. One billionaire moving into a small town rockets the mean income while the median barely moves. Skewed data — incomes, house prices, response times — is usually summarised more honestly by the median; symmetric data by either.

How much data does this handle?

Thousands of values comfortably — it is a single pass of arithmetic in your browser. The practical limit is pasting, not computing. It needs at least two values, since spread is meaningless for one.

References