X-Nico

68–95–99.7 rule

In statistics, the 68–95–99.7 rule, also known as the three-sigma rule or empirical rule, states that nearly all values lie within three standard deviations of the mean in a normal distribution.

SOFA Statistics

Nested tables can be produced with row and column percentages, totals, sd, mean, median, lower and upper quartiles, and sum.

Strictly standardized mean difference

In a primary screen without replicates, assuming the measured value (usually on the log scale) in a well for a tested compound is $X\; i$ and the negative reference in that plate has sample size $n\; N$, sample mean $\backslash bar\{X\}\; N$, median $\backslash tilde\{X\}\; N$, standard deviation $s\; N$ and median absolute deviation $\backslash tilde\{s\}\; N$, the SSMD for this compound is estimated as

Vysochanskij–Petunin inequality

In probability theory, the Vysochanskij–Petunin inequality gives a lower bound for the probability that a random variable with finite variance lies within a certain number of standard deviations of the variable's mean, or equivalently an upper bound for the probability that it lies further away.

see also

Active contour model

Where $G\; \{\backslash sigma\}$ is a Gaussian standard deviation $\backslash sigma$ minima of this functional lie on zero-crossings of

Bessel's correction

In statistics, Bessel's correction, named after Friedrich Bessel, is the use of n − 1 instead of n in the formula for the sample variance and sample standard deviation, where n is the number of observations in a sample: it corrects the bias in the estimation of the population variance, and some (but not all) of the bias in the estimation of the population standard deviation.

Studentification

Studentization — adjustment of a statistic by dividing it by a sample-based estimate of its standard deviation.