Section author: Ravi Selker, Jonathon Love, Damian Dropmann

Proportion Test (N Outcomes; propTestN)

Description

The X² Goodness of fit test (not to be confused with the X² test of independence), tests the Null hypothesis that the proportions of observations match some expected proportions. If the p-value is low, this suggests that the Null hypothesis is false, and that the true proportions are different to those tested.

Usage

propTestN(
    data,
    var,
    counts = NULL,
    expected = FALSE,
    ratio = NULL,
    formula)

Arguments

data	the data as a data frame
var	the variable of interest in data (not necessary when using a formula, see the examples)
counts	the counts in data
expected	TRUE or FALSE (default), whether expected counts should be displayed
ratio	a vector of numbers: the expected proportions
formula	(optional) the formula to use, see the examples

Output

A results object containing:

results$props	a table of the proportions
results$tests	a table of the test results

Tables can be converted to data frames with asDF or as.data.frame(). For example:

results$props$asDF

as.data.frame(results$props)

Examples

data('HairEyeColor')
dat <- as.data.frame(HairEyeColor)

propTestN(formula = Freq ~ Eye, data = dat, ratio = c(1,1,1,1))

#
#  PROPORTION TEST (N OUTCOMES)
#
#  Proportions
#  --------------------------------
#    Level    Count    Proportion
#  --------------------------------
#    Brown      220         0.372
#    Blue       215         0.363
#    Hazel       93         0.157
#    Green       64         0.108
#  --------------------------------
#
#
#  X² Goodness of Fit
#  -----------------------
#    X²     df    p
#  -----------------------
#    133     3    < .001
#  -----------------------
#