Quick Answer
For the data set {2, 4, 4, 4, 5, 5, 7, 9}, the mean is 5, the population standard deviation is 2, and the sample standard deviation is approximately 2.14.
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Common Examples
| Input | Result |
|---|---|
| 2, 4, 4, 4, 5, 5, 7, 9 | Mean: 5, Pop SD: 2.0, Sample SD: 2.14 |
| 10, 12, 23, 23, 16, 23, 21, 16 | Mean: 18, Pop SD: 4.90, Sample SD: 5.24 |
| 1, 2, 3, 4, 5 | Mean: 3, Pop SD: 1.41, Sample SD: 1.58 |
| 100, 100, 100 | Mean: 100, Pop SD: 0, Sample SD: 0 |
How It Works
Mean (Average) = Sum of all values / N
Population Standard Deviation
σ = √(Σ(xᵢ − μ)² / N)
Where μ is the population mean and N is the total number of values. Use this when your data represents the entire population.
Sample Standard Deviation
s = √(Σ(xᵢ − x̄)² / (N − 1))
Where x̄ is the sample mean. Dividing by N − 1 instead of N is known as Bessel’s correction, which compensates for the bias in estimating a population variance from a sample.
Variance is the square of the standard deviation. Population variance divides by N; sample variance divides by N − 1.
Median is the middle value when the data is sorted in ascending order. For an even number of values, the median is the average of the two middle values.
Range = Maximum value − Minimum value
Worked Example
For the data set {2, 4, 4, 4, 5, 5, 7, 9}: Mean = (2+4+4+4+5+5+7+9)/8 = 40/8 = 5. Squared deviations: (2-5)²=9, (4-5)²=1, (4-5)²=1, (4-5)²=1, (5-5)²=0, (5-5)²=0, (7-5)²=4, (9-5)²=16. Sum = 32. Population variance = 32/8 = 4, so population SD = sqrt(4) = 2. Sample variance = 32/7 ≈ 4.571, so sample SD ≈ 2.14.
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