
A measure of the amount of variation or dispersion of a set of values from its mean.Standard deviation is a statistical measure that quantifies the amount of variation or dispersion in a set of values. It tells you how spread out the numbers are around the mean (average). A small standard deviation means the values are clustered closely, while a large one indicates wide spread. In physics, it is used to characterize the uncertainty in measurements, the spread of particle velocities in a gas, or the noise in experimental data.
The concept was introduced by Karl Pearson in 1894, building on earlier work by Gauss and others on the normal distribution and least squares methods.
To compute it, you take the square root of the variance, which is the average of the squared differences from the mean. This gives a value in the same units as the original data, making it intuitive. In a normal distribution, about 68% of values lie within one standard deviation of the mean, 95% within two, and 99.7% within three—a rule of thumb used widely in quality control and error analysis.
Standard deviation is used in experimental physics to report measurement uncertainties, in particle physics to identify significant deviations from background noise, and in engineering to set tolerance limits.
The standard deviation of the cosmic microwave background temperature fluctuations is about 18 microkelvins, a tiny number that encodes the seeds of all structure in the universe.
| \Delta\theta | variable | Standard deviation of the estimator for parameter theta — standard deviation |
| \mathcal{F}(\rho_\th | variable | Quantum Fisher information of the state rho_theta — quantum fisher information |
| f(x_i) | variable | model prediction at input x_i — function value |
| y_i | variable | observed data point — data value |
| σ_i | variable | standard deviation of measurement error — standard deviation |
| ∏ | operator | Product over all data points i — product operator |
| exp | operator | Exponential function — exponential function |
| P(D|θ) | variable | probability of data given parameters — probability |
| y_model | variable | model prediction — value |
| y_data | variable | observed data point — value |
| σ | variable | standard deviation of Gaussian noise — standard deviation |
| log | operator | natural logarithm — logarithm |
| ∑ | operator | sum over all data points — summation |
| c | variable | cross-correlation value — cross correlation |
| v | variable | Doppler shift velocity — velocity metre per second |
| λ | variable | wavelength — wavelength metre |
| S1 | variable | first spectrum — spectrum |
| S2 | variable | second spectrum — spectrum |
| S̄1 | variable | mean of first spectrum over wavelength — mean spectrum |
| S̄2 | variable | mean of second spectrum over wavelength — mean spectrum |
| σ | variable | standard deviation of spectrum — standard deviation |
| ∑ | operator | sum over wavelength bins — summation |





