この節の作者: 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
# -----------------------
#