HH (version 3.1-47)

normalApproxBinomial: Plots to illustrate Normal Approximation to the Binomial---hypothesis tests or confidence intervals.

Description

Plots to illustrate Normal Approximation to the Binomial---hypothesis tests or confidence intervals.

Usage

normalApproxBinomial(p0= if (number.vars==1) .5 else 0,
                     p1=NA, p2=NA,
                     p.hat=if (number.vars==1) .75 else 0,
                     n=1,
                     xlim=if (number.vars==1) c(0,1) else c(-1,1),
                     ylim=c(0, 5),
                     type=c("hypothesis","confidence"),
                     alpha.left=if (type=="hypothesis") 0 else .025,
                     alpha.right=if (type=="hypothesis") .05 else .025,
                     xlab=if (number.vars==1)
                            "w = p = population proportion"
                          else
                            "w = p[1] - p[2] :: population proportions", ...,
                     number.vars=if (!is.na(p1) && !is.na(p2)) 2 else 1)

Arguments

p0

Null hypothesis value of \(p\).

p1

Alternate hypothesis value of \(p\) for one-sample cases. Second sample value of \(p\) for two-sample cases.

p2

Second sample value of \(p\).

p.hat

Observed value of \(p\).

n

Number of observations (for example, number of coins tossed).

xlim, ylim, xlab

Standard xyplot arguments...

type

"hypothesis" for a Hypothesis Test graph, or "confidence" for a Confidence Interval graph.

…, alpha.left, alpha.right

Additional arguments forwarded to NTplot.

number.vars

Number of variables. 1 for a one-sample test, 2 for two-sample tests and paired tests.

Value

"trellis" object.

Details

This is a wrapper function for the plots in NTplot.

Examples

# NOT RUN {
NTplot(distribution.name="binomial", n=20, ylim=c(0,4.2), p1=.8)
NTplot(distribution.name="binomial", n=20, type="confidence", ylim=c(0,4.2))
# }
# NOT RUN {
NTplot(distribution.name="binomial", n=20, zaxis=TRUE, z1axis=TRUE,
       p1=.8678, ylim=c(0, 5.2))
NTplot(p0=.4, p.hat=.65, p1=.7, distribution.name="binomial", n=15)
NTplot(p.hat=.65, distribution.name="binomial", n=15, type="confidence")
# }
# NOT RUN {
 ## these are interactive and won't work in R CMD check
  if (interactive())
    NTplot(distribution.name="binomial", n=20, ylim=c(0,4.2), p1=.8, shiny=TRUE)
  if (interactive())
    NTplot(p0=.4, p.hat=.65, p1=.7, distribution.name="binomial", n=15, shiny=TRUE)
  if (interactive())
    NTplot(p.hat=.65, distribution.name="binomial", n=15, type="confidence", shiny=TRUE)
# }