cnorm: Central Probability in a Normal or T Distribution

In mosaic: Project MOSAIC Statistics and Mathematics Teaching Utilities

Central Probability in a Normal or T Distribution

Description

These versions of the quantile functions take a vector of central probabilities as its first argument.

Usage

cnorm(p, mean = 0, sd = 1, log.p = FALSE, side = c("both", "upper", "lower"))

ct(p, df, ncp, log.p = FALSE, side = c("upper", "lower", "both"))

Arguments

p	vector of probabilities.
mean	vector of means.
sd	vector of standard deviations.
log.p	logical. If TRUE, uses the log of probabilities.
side	One of "upper", "lower", or "both" indicating whether a vector of upper or lower quantiles or a matrix of both should be returned.
df	degrees of freedom (> 0, maybe non-integer). df = Inf is allowed.
ncp	non-centrality parameter \delta; currently except for rt(), only for abs(ncp) <= 37.62. If omitted, use the central t distribution.

See Also

stats::qnorm(), cdist()

Examples

qnorm(.975)
cnorm(.95)
xcnorm(.95)
xcnorm(.95, verbose = FALSE, return = "plot") |>
  gf_refine(
  scale_fill_manual( values = c("navy", "limegreen")),
  scale_color_manual(values = c("black", "black")))
cnorm(.95, mean = 100, sd = 10)
xcnorm(.95, mean = 100, sd = 10)

mosaic documentation built on Nov. 10, 2023, 1:11 a.m.