Statistics⏱ 6 min read

Standard Deviation

σ = √(Σ(x−μ)² / n)

📖 What is Standard Deviation?

Standard deviation measures how spread out data values are from the mean. A small standard deviation means values are clustered close together; a large one means they are spread far apart.

σ = √( Σ(xᵢ − μ)² / n )

🔤 What Each Symbol Means

σ
Standard deviation (sigma)The measure of spread we're calculating
μ
Mean (mu)The average of all data values
xᵢ
Each data valueEvery individual value in the dataset
n
Number of valuesTotal count of data points (use n-1 for sample std dev)

📝 Step-by-Step Example

Find the standard deviation of {2, 4, 4, 4, 5, 5, 7, 9}.

1
Find the meanμ = (2+4+4+4+5+5+7+9)/8 = 40/8 = 5
2
Subtract mean from each value, then square(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
3
Sum the squared differences9+1+1+1+0+0+4+16 = 32
4
Divide by n, then take square rootσ = √(32/8) = √4
Answer: σ = 2

💡 Population vs Sample

Population std dev (σ):
Divide by n — use when you have ALL data
Sample std dev (s):
Divide by (n−1) — use when you have a subset of data
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🎯 Quick Fact

In a normal distribution, about 68% of values fall within 1 standard deviation of the mean, and 95% within 2 standard deviations.