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Standard Deviation Calculator

Calculate standard deviation, variance, and other statistical measures for your dataset.

Enter Your Data
Provide numerical data points separated by commas

Enter numbers separated by commas. Example: 23, 45, 67, 89, 12, 34, 56, 78, 90, 11

Statistical Results
Based on your dataset analysis

Enter your data points and click "Calculate Standard Deviation" to see your results

About Standard Deviation

What is Standard Deviation?

Standard deviation is a measure of the amount of variation or dispersion in a set of values. A low standard deviation indicates that the values tend to be close to the mean, while a high standard deviation indicates that the values are spread out over a wider range.

How Standard Deviation is Calculated

Population Standard Deviation Formula:

σ = √[Σ(x - μ)²/N]

Where:

  • • σ = standard deviation
  • • Σ = sum of
  • • x = each value in the dataset
  • • μ = mean of the dataset
  • • N = number of values in the dataset

Population vs Sample Standard Deviation

Population Standard Deviation

  • • Used when you have data for the entire population
  • • Denominator is N (total number of values)
  • • Symbol: σ (sigma)
  • • Formula: σ = √[Σ(x - μ)²/N]

Sample Standard Deviation

  • • Used when you have a sample of the population
  • • Denominator is N-1 (Bessel's correction)
  • • Symbol: s
  • • Formula: s = √[Σ(x - μ)²/(N-1)]

Interpreting Standard Deviation

  • Normal Distribution: In a normal distribution, approximately 68% of values fall within 1 standard deviation of the mean, 95% within 2 standard deviations, and 99.7% within 3 standard deviations.
  • Low Standard Deviation: Values are clustered closely around the mean, indicating consistency and low variability.
  • High Standard Deviation: Values are spread out over a wider range, indicating high variability and diversity in the dataset.
  • Zero Standard Deviation: All values in the dataset are identical.

Applications of Standard Deviation

  • Finance: Measuring investment risk and volatility
  • Quality Control: Monitoring manufacturing processes and product consistency
  • Research: Analyzing experimental data and statistical significance
  • Education: Grading on a curve and assessing student performance
  • Weather: Analyzing temperature variations and climate patterns
  • Sports: Evaluating player performance consistency

Tips for Using This Calculator

  • Enter numbers separated by commas (e.g., 1, 2, 3, 4, 5)
  • Ensure all values are numerical - non-numeric values will be ignored
  • Use decimal points for precise values (e.g., 3.14, 2.718)
  • The calculator works with both positive and negative numbers
  • For large datasets, consider using statistical software for more advanced analysis
  • Remember the difference between population and sample standard deviation when interpreting results