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Calculate statistical measures including variance, mean, median, and more
In a normal distribution, 68% of data falls within 1 SD, 95% within 2 SDs, and 99.7% within 3 SDs of the mean.
Standard deviation measures investment volatility. Higher SD means more risk but potentially higher returns.
Six Sigma methodology uses SD to reduce defects to 3.4 per million, revolutionizing manufacturing quality.
SD helps scientists understand genetic variation in populations and identify unusual mutations.
Climate scientists use SD to measure temperature variability and identify extreme weather patterns.
Teams use SD to analyze player consistency. A low SD indicates a reliable performer game after game.
IQ tests use SD of 15 points. A score of 130 is 2 standard deviations above average (top 2.3%).
Casinos use SD to predict profit margins. More games played means results converge to expected values.
Standard deviation measures how spread out numbers are from the mean. A low SD indicates values cluster close to the mean, while high SD indicates values are spread over a wider range. Sample SD (n-1 divisor) is used when calculating from a sample, while population SD (n divisor) is used when you have all values in a population.