TDist {base}R Documentation

The Student t Distribution

Description

These functions provide information about the t distribution with df degrees of freedom (and optional noncentrality parameter ncp). dt gives the density, pt gives the distribution function, qt gives the quantile function and rt generates random deviates.

Usage

dt(x, df)
pt(q, df, ncp=0)
qt(p, df)
rt(n, df)

Arguments

x,q vector of quantiles.
p vector of probabilities.
n number of observations to generate.
df degrees of freedom (> 0, maybe non-integer).
ncp non-centrality parameter delta; currently ncp <= 37.62.

Details

The t distribution with df = n degrees of freedom has density

f(x) = Gamma((n+1)/2) / (sqrt(n pi) Gamma(n/2)) (1 + x^2/n)^-((n+1)/2)

for all real x. It has mean 0 (for n > 1) and variance n/(n-2) (for n > 2).

The general non-central t with parameters (df,Del) = (df, ncp) is defined as a the distribution of T(df,Del) := (U + Del) / (Chi(df) / sqrt(df)) where U and Chi(df) are independent random variables, U ~ N(0,1), and Chi(df)^2 is chi-squared, see pchisq.

The most used applications are power calculations for t-tests:
Let T= (mX - m0) / (S/sqrt(n)) where mX is the mean and S the sample standard deviation (sd) of X_1,X_2,...,X_n which are i.i.d. N(mu,sigma^2). Then T is distributed as non-centrally t with df= n-1 degrees of freedom and non-centrality parameter ncp= mu - m0.

References

Lenth, R. V. (1989). Algorithm AS 243 – Cumulative distribution function of the non-central t distribution, Appl. Statist. 38, 185𤪭.

See Also

df for the F distribution.

Examples

1 - pt(1:5, df = 1)
qt(.975, df = c(1:10,20,50,100,1000))

tt <- seq(0,10, len=21)
ncp <- seq(0,6, len=31)
ptn <- outer(tt,ncp, function(t,d) pt(t, df = 3, ncp=d))
image(tt,ncp,ptn, zlim=c(0,1),main=t.tit <- "Non-central t - Probabilities")
persp(tt,ncp,ptn, zlim=0:1, r=2, phi=20, theta=200, main=t.tit)


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