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Library / Statistics / STA-01

Statistics

Sample mean

The average: total of the readings divided by how many there are.

Ref
STA-01
Rev
v1
Field
Statistics
Result
x̄

Σx is the total of all the readings and n the number of readings. The mean is the balance point of the data. It is a sample estimate of the true average, with uncertainty given by the standard error.

The average: total of the readings divided by how many there are.

Calculator

Solve for
110,000
11,000
  • New mean if one extra reading of 2 × the mean is added27.27
  • Share of the mean carried by each reading10 %

What drives the result

Each variable is moved across its typical range while the others stay at the values above. The longest bar is the key driver.

Mean () current value 25
ΣxSum of readingsKey driver
0.11,000
nNumber of readings
0.25250
  • Each of the ten default readings carries 10 % of the mean, so an outlier pulls the mean far more in a small sample than in a large one.
  • The mean says nothing about spread; two data sets can share a mean and differ widely in scatter.
Chart data as tables

Ranked variables

VariableTypical rangeLowest resultHighest resultSwing ()Local stepChange in result
Σx Sum of readings1 to 10,000 0.11,000999.9+10%+10 %
n Number of readings1 to 1,000 0.25250249.8+1 −9.09 %

Sweep of Number of readings

Number of readingsMean
1250
2.371105.4
5.62344.46
13.3418.75
31.627.906
74.993.334
177.81.406
421.70.5928
1,0000.25

Sweep one variable

Mean ()Hover, touch, or use the arrow keys on the chart
050100150200250 1520100500 Number of readings, log scale now 25

Variables and how each one contributes

x̄

Mean

Result ·

What the equation gives you. Everything else feeds it.

Σx

Sum of readings

· typical 1 to 10,000

The sum of all the readings. Directly proportional: one large reading pulls the mean up by its share of the extra.

n

Number of readings

· typical 1 to 1,000

How many readings were taken. Inversely proportional for a fixed total; more readings of the same total spread the value more thinly.

Worked example with the values above

  1. Add up the readings: Σx = 250.
  2. Count them: n = 10.
  3. x̄ = 250 / 10 = 25.

Assumptions and limits

  • The readings come from one process and are equally trustworthy.
  • No reading has been left out or recorded twice.

Common mistakes

  • Dividing by n − 1; that is for the sample variance, not for the mean.
  • Averaging averages from groups of different size without weighting.

Statistics and uncertainty

The sample mean is itself an estimate. Its uncertainty is the standard error s/√n, so the mean of a small sample can sit well away from the true value.

Where it is used

  • Typical value of repeated range-test readings.
  • Average of repeated measurements to reduce random error.

Maths you need

  • Sums: Σ notation
  • Division: total divided by count

Related formulas

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