These functions behave similarly to the functions with the initial x
removed from their names but add more verbose output and graphics.
xpnorm(
q,
mean = 0,
sd = 1,
plot = TRUE,
verbose = TRUE,
invisible = FALSE,
digits = 4,
lower.tail = TRUE,
log.p = FALSE,
xlim = mean + c(-4, 4) * sd,
ylim = c(0, 1.4 * dnorm(mean, mean, sd)),
manipulate = FALSE,
...,
return = c("value", "plot")
)
xqnorm(
p,
mean = 0,
sd = 1,
plot = TRUE,
verbose = TRUE,
digits = getOption("digits"),
lower.tail = TRUE,
log.p = FALSE,
xlim,
ylim,
invisible = FALSE,
...,
return = c("value", "plot"),
pattern = c("stripes", "rings")
)
xcnorm(
p,
mean = 0,
sd = 1,
plot = TRUE,
verbose = TRUE,
digits = getOption("digits"),
lower.tail = TRUE,
log.p = FALSE,
xlim,
ylim,
invisible = FALSE,
...,
return = c("value", "plot"),
pattern = "rings"
)Arguments
- q
quantile
- mean, sd
parameters of normal distribution.
- plot
logical. If TRUE, show an illustrative plot.
- verbose
logical. If TRUE, display verbose output.
- invisible
logical. If TRUE, return value invisibly.
- digits
number of digits to display in output.
- lower.tail
logical. If FALSE, use upper tail probabilities.
- log.p
logical. If TRUE, uses the log of probabilities.
- xlim, ylim
limits for plotting.
- manipulate
logical. If TRUE and in RStudio, then sliders are added for interactivity.
- ...
additional arguments.
- return
If
"plot", return a plot. If"values", return a vector of numerical values.- p
probability
- pattern
One of
"stripes"or"rings". In the latter case, pairs of regions (from inside to outside) are grouped together for coloring and probability calculation.
See also
histogram(),
chisq.test(),
pnorm(),
qnorm(),
qqmath(), and
plot().
Examples
xpnorm(650, 500, 100)
#>
#> If X ~ N(500, 100), then
#> P(X <= 650) = P(Z <= 1.5) = 0.9332
#> P(X > 650) = P(Z > 1.5) = 0.06681
#>
#> [1] 0.9331928
xqnorm(.75, 500, 100)
#>
#> If X ~ N(500, 100), then
#> P(X <= 567.449) = 0.75
#> P(X > 567.449) = 0.25
#>
#> [1] 567.449
xpnorm(-3:3, return = "plot", system = "gg") |>
gf_labs(title = "My Plot", x = "") |>
gf_theme(theme_bw())
#>
#> If X ~ N(0, 1), then
#> P(X <= -3) = P(Z <= -3) = 0.00135 P(X <= -2) = P(Z <= -2) = 0.02275 P(X <= -1) = P(Z <= -1) = 0.15866 P(X <= 0) = P(Z <= 0) = 0.50000 P(X <= 1) = P(Z <= 1) = 0.84134 P(X <= 2) = P(Z <= 2) = 0.97725 P(X <= 3) = P(Z <= 3) = 0.99865
#> P(X > -3) = P(Z > -3) = 0.99865 P(X > -2) = P(Z > -2) = 0.97725 P(X > -1) = P(Z > -1) = 0.84134 P(X > 0) = P(Z > 0) = 0.50000 P(X > 1) = P(Z > 1) = 0.15866 P(X > 2) = P(Z > 2) = 0.02275 P(X > 3) = P(Z > 3) = 0.00135
#>
if (FALSE) {
if (rstudio_is_available() & require(manipulate)) {
manipulate(xpnorm(score, 500, 100, verbose = verbose),
score = slider(200, 800),
verbose = checkbox(TRUE, label = "Verbose Output")
)
}
}