exams.forge (version 1.0.10)

t2norm: Approximations

Description

Functions which deliver TRUE or FALSE if any approximation if possible. The approximation parameter c can be set directly, or it can be given via getOption. The approximation functions deliver TRUE in the following scenarios:

• t2norm: n>c with c=30

• binom2norm: if the type is "single" (default) then it checks size × prob (1-prob)>c, or else it checks size × prob>c and size × (1-prob)>c with c=9

• clt2norm: n>c with c=30. Note that the existence of the expectation and variance, which are required by the Central Limit Theorem, cannot be checked. ``

Usage

t2norm(n, c = getOption("distribution.t2norm", 30))
binom2norm(
  size,
  prob,
  c = getOption("distribution.binom2norm", 9),
  type = c("single", "double")
)
clt2norm(n, c = getOption("distribution.clt2norm", 30))
approx_binom2norm(
  size,
  prob,
  c = getOption("distribution.binom2norm", 9),
  type = c("single", "double")
)
approx_clt2norm(n, c = getOption("distribution.clt2norm", 30))
approx_t2norm(n, c = getOption("distribution.t2norm", 30))

Value

logical if the approximation would be possible

Arguments

n

integer: number of observations

c

numeric: approximation parameter (default: getOption("distribution.APPROXFUN) or a default value)

size

integer: number of observations

prob

numeric: probability of success on each trial

type

character: approximation condition used

Examples

# check for 5 observations
t2norm(n=c(5,50))
binom2norm(size=c(5,50), prob=0.5)
binom2norm(size=c(5,50), prob=0.5, type="double")