Calculadora de Desvio Padrão
Calcule o desvio padrão populacional e amostral com resultados passo a passo
Standard Deviation Calculator
Calculate standard deviation and variance
Enter comma-separated numbers
sigma = sqrt(sum((xi - mean)^2) / N)What is a Standard Deviation Calculator?
A Standard Deviation Calculator is a statistics tool that measures how spread out a set of numbers is. Standard deviation tells you, on average, how far the values in a dataset are from the mean (average). A small standard deviation means the numbers are close together and close to the mean. A large standard deviation means the numbers vary widely.
Standard deviation is one of the most important ideas in statistics because it describes variability. It's used in many real-world areas such as finance (volatility of returns), education (spread of test scores), science (measurement error and consistency), and business analytics (variation in sales or performance metrics).
This calculator helps you compute standard deviation quickly and accurately—especially for larger datasets—without manually doing multiple steps like finding the mean, subtracting values, squaring differences, and taking square roots.
This Calculator Outputs Both Modes
- Population StdDev -- use when your data includes every member of the group
- Sample StdDev -- use when your data is a subset (sample) of a larger population
- Variance -- the square of the standard deviation (population variance)
How to Use This Standard Deviation Calculator
- Enter your data values -- input numbers into the data field (numbers only)
- Separate values using commas -- for example: 5, 10, 15, 20, 25
- Click 'Calculate' -- to compute the standard deviation
- Review the results -- both Population StdDev and Sample StdDev are displayed, along with Variance
- Interpret the spread -- compare the standard deviation relative to the mean to understand how consistent or varied the data is
Tips:
- Use Population when your data includes every member of the group you're measuring
- Use Sample when your data is a subset (sample) taken from a larger population
- Standard deviation is in the same units as your data (unlike variance, which is in squared units)
Standard Deviation Formulas
Let your dataset be: x₁, x₂, x₃, …, xₙ where n is the number of values.
Mean (Average)
x̄ = (x₁ + x₂ + … + xₙ) / n
Sum all values, then divide by the count
Population Standard Deviation
Variance:
σ² = [ Σ(xᵢ − μ)² ] / n
Standard deviation:
σ = √σ²
μ = population mean; divide by n
Sample Standard Deviation
Variance:
s² = [ Σ(xᵢ − x̄)² ] / (n − 1)
Standard deviation:
s = √s²
x̄ = sample mean; divide by (n − 1)
Why divide by (n − 1) for a sample?
Using (n − 1) instead of n corrects bias when estimating population variability from a sample. This adjustment is called Bessel's correction and produces a more accurate estimate of the true population standard deviation.
Example Calculations
Example 1: Population Standard Deviation
Data: 1, 2, 3
Mean (μ): (1 + 2 + 3) / 3 = 2
Differences from mean: (1−2) = −1, (2−2) = 0, (3−2) = 1
Squared → Sum: 1 + 0 + 1 = 2
σ²: 2 / 3 = 0.6667
σ: √0.6667 ≈ 0.8165
Result: Population SD ≈ 0.8165
Example 2: Sample Standard Deviation
Data: 1, 2, 3
Mean: 2, squared differences sum: 2
s²: 2 / (3 − 1) = 2 / 2 = 1
s: √1 = 1
Result: Sample SD = 1
Example 3: Low vs High Variability Comparison
Dataset A: 9, 10, 10, 11 (values close together)
Dataset B: 2, 6, 14, 18 (values spread out)
Both sets have a mean of 10, but Dataset B has a much larger standard deviation because values are farther from the mean.
Result: Higher spread → higher standard deviation
Example 4: Real-World Example (Test Scores)
Scores: 78, 80, 82, 85, 95
The mean is around the low-to-mid 80s. The score 95 is farther from the mean and increases the spread.
Result: The standard deviation helps quantify how consistent (or inconsistent) the scores are.
Frequently Asked Questions
What does standard deviation tell me?
It tells you how much values typically vary from the mean. Lower standard deviation means the data is clustered; higher standard deviation means the data is more spread out.
What's the difference between variance and standard deviation?
Variance is the average of squared differences from the mean. Standard deviation is the square root of variance. Standard deviation is preferred because it's in the same units as the original data.
Should I use sample or population standard deviation?
Use population if you have the full group you care about. Use sample if your data is only part of a larger group and you're estimating the population variability.
Can standard deviation be zero?
Yes. If all numbers are the same (e.g., 5, 5, 5, 5), there is no variation, so the standard deviation is 0.
How do outliers affect standard deviation?
Outliers (very high or very low values) usually increase standard deviation because they are far from the mean and contribute large squared differences.
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O que é desvio padrão?
O desvio padrão mede o quanto os valores de um conjunto de dados estão dispersos em relação à sua média. Um desvio padrão baixo significa que os valores se concentram perto da média; um alto indica que estão muito espalhados. É uma das estatísticas mais usadas no mundo — aparece em finanças (volatilidade de ações), ciência (margens de erro experimental), educação (distribuição de notas) e controle de qualidade industrial.
Existem dois tipos: desvio padrão populacional (σ) quando o conjunto de dados inclui todos os membros do grupo, e desvio padrão amostral (s) quando você trabalha com um subconjunto extraído de uma população maior. Esta calculadora computa ambos, junto com a variância e a média, a partir de qualquer lista de números que você fornecer.
Como usar a calculadora de desvio padrão
- Digite ou cole seus números no campo de entrada, separados por vírgulas (ex.: 4, 7, 13, 2, 1).
- Escolha se deseja o desvio padrão populacional ou amostral — ou deixe a calculadora mostrar os dois.
- Clique em Calcular para executar o cálculo.
- Leia o desvio padrão, a variância e a média no painel de resultados.
Fórmula do desvio padrão
Média: μ = Σx / n
Desvio Padrão Pop. σ: √(Σ(x − μ)² / n)
Desvio Padrão Amostral s: √(Σ(x − μ)² / (n − 1))
Variância (pop.): σ² = Σ(x − μ)² / n
Variância (amostral): s² = Σ(x − μ)² / (n − 1)Use σ populacional quando seus dados SÃO toda a população (ex.: todas as notas de uma turma). Use s amostral quando seus dados são um subconjunto de uma população maior (ex.: uma pesquisa com 500 pessoas representando milhões). A fórmula amostral divide por (n − 1) em vez de n — chamada correção de Bessel — para produzir uma estimativa sem viés da dispersão real da população.
Exemplos resolvidos
Exemplo 1 — Conjunto clássico: {2, 4, 4, 4, 5, 5, 7, 9}
Média = (2+4+4+4+5+5+7+9) / 8 = 40 / 8 = 5. A soma dos desvios quadráticos em relação a 5 é 32. Desvio padrão populacional σ = √(32/8) = √4 = 2,00. Este é um conjunto de dados clássico que ilustra exatamente σ = 2.
Exemplo 2 — Valores igualmente espaçados: {10, 20, 30, 40, 50}
Média = 150 / 5 = 30. Soma dos desvios quadráticos = (20²+10²+0²+10²+20²) = 1000. σ populacional = √(1000/5) = √200 ≈ 14,14. s amostral = √(1000/4) = √250 ≈ 15,81.
Exemplo 3 — Sem dispersão: {100, 100, 100}
Média = 100. Cada valor é igual à média, então cada desvio quadrático é 0. Desvio padrão = 0: não há nenhuma dispersão neste conjunto de dados. Isso acontece sempre que todos os valores são idênticos.