Student's t-Distribution

DESCRIPTION:
Density, cumulative probability, quantiles and random generation for Student's t distribution.

USAGE:
dt(x, df)
pt(q, df)
qt(p, df)
rt(n, df)

REQUIRED ARGUMENTS:
x:
vector of quantiles. Missing values (NAs) are allowed.
q:
vector of quantiles. Missing values (NAs) are allowed.
p:
vector of probabilities. Missing values (NAs) are allowed.
n:
sample size. If length(n) is larger than 1, then length(n) random values are returned.
df:
vector of degrees of freedom. This is replicated to be the same length as p or q or the number of deviates generated.

VALUE:
density (dt), probability (pt), quantile (qt), or random sample (rt) for Student's t-distribution on df degrees of freedom.

SIDE EFFECTS:
The function rt causes creation of the dataset .Random.seed if it does not already exist, otherwise its value is updated.

DETAILS:
Elements of q or p that are missing will cause the corresponding elements of the result to be missing.

BACKGROUND:
Student's t is a real valued distribution symmetric about 0. The t approaches the Gaussian (normal) distribution as the degrees of freedom go to infinity. The major use of the t is to test hypotheses and construct confidence intervals for means of Gaussian data.

REFERENCES:
Johnson, N. L. and Kotz, S. (1970). Continuous Univariate Distributions, vol. 2. Houghton-Mifflin, Boston.

SEE ALSO:
F , Normal , .Random.seed , set.seed .

EXAMPLES:
(1 - pt(abs(x)))*2 # two-tailed p-value for x