TDist {stats} R Documentation

## The Student t Distribution

### Description

Density, distribution function, quantile function and random generation for the t distribution with `df` degrees of freedom (and optional noncentrality parameter `ncp`).

### Usage

```dt(x, df, ncp=0, log = FALSE)
pt(q, df, ncp=0, lower.tail = TRUE, log.p = FALSE)
qt(p, df,        lower.tail = TRUE, log.p = FALSE)
rt(n, df)
```

### Arguments

 `x, q` vector of quantiles. `p` vector of probabilities. `n` number of observations. If `length(n) > 1`, the length is taken to be the number required. `df` degrees of freedom (> 0, maybe non-integer). `ncp` non-centrality parameter delta; currently for `pt()` and `dt()`, only for `ncp <= 37.62`. `log, log.p` logical; if TRUE, probabilities p are given as log(p). `lower.tail` logical; if TRUE (default), probabilities are P[X <= x], otherwise, P[X > x].

### 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 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) * sqrt(n)/sigma.

### Value

`dt` gives the density, `pt` gives the distribution function, `qt` gives the quantile function, and `rt` generates random deviates.

### References

Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole. (except non-central versions.)

Lenth, R. V. (1989). Algorithm AS 243 — Cumulative distribution function of the non-central t distribution, Appl. Statist. 38, 185–189.

`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,
xlab = "t", ylab = "noncentrality parameter", zlab = "Pr(T <= t)")

op <- par(yaxs="i")
plot(function(x) dt(x, df = 3, ncp = 2), -3, 11, ylim = c(0, 0.32),
main="Non-central t - Density")
par(op)
```

[Package stats version 2.1.0 Index]