A statistical distribution published by William Gosset in 1908. His employer, Guinness Breweries, required him to publish under a pseudonym, so he chose "Student." Given independent measurements , let
(1)

where is the population mean, is the sample mean, and is the estimator for population standard deviation (i.e., the sample variance) defined by
(2)

Student's distribution is defined as the distribution of the random variable which is (very loosely) the "best" that we can do not knowing .
The Student's distribution with degrees of freedom is implemented in the Wolfram Language as StudentTDistribution[n].
If , and the distribution becomes the normal distribution. As increases, Student's distribution approaches the normal distribution.
Student's distribution can be derived by transforming Student's zdistribution using
(3)

and then defining
(4)

The resulting probability and cumulative distribution functions are
(5)
 
(6)
 
(7)
 
(8)
 
(9)

where
(10)

is the number of degrees of freedom, , is the gamma function, is the beta function, is a hypergeometric function, and is the regularized beta function defined by
(11)

The mean, variance, skewness, and kurtosis excess of Student's distribution are
(12)
 
(13)
 
(14)
 
(15)

The characteristic functions for the first few values of are
(16)
 
(17)
 
(18)
 
(19)
 
(20)

and so on, where is a modified Bessel function of the second kind.
The following table gives confidence intervals, i.e., values of such that the distribution function equals various probabilities for various small values of the numbers of degrees of freedom . Beyer (1987, p. 571) gives 60%, 70%, 90%, 95%, 97.5%, 99%, 99.5%, and 99.95% confidence intervals, and Goulden (1956) gives 50%, 90%, 95%, 98%, 99%, and 99.9% confidence intervals.
90%  95%  97.5%  99.5%  
1  3.07768  6.31375  12.7062  63.6567 
2  1.88562  2.91999  4.30265  9.92484 
3  1.63774  2.35336  3.18245  5.84091 
4  1.53321  2.13185  2.77645  4.60409 
5  1.47588  2.01505  2.57058  4.03214 
10  1.37218  1.81246  2.22814  3.16927 
30  1.31042  1.69726  2.04227  2.75000 
100  1.29007  1.66023  1.98397  2.62589 
1.28156  1.64487  1.95999  2.57588 
A multivariate form of the Student's distribution with correlation matrix and degrees of freedom is implemented as MultivariateTDistribution[r, m] in the Wolfram Language package MultivariateStatistics` .
The socalled distribution is useful for testing if two observed distributions have the same mean. gives the probability that the difference in two observed means for a certain statistic with degrees of freedom would be smaller than the observed value purely by chance:
(21)

Let be a normally distributed random variable with mean 0 and variance , let have a chisquared distribution with degrees of freedom, and let and be independent. Then
(22)

is distributed as Student's with degrees of freedom.