propTestN | R Documentation |
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.
propTestN(data, var, counts = NULL, expected = FALSE, ratio = NULL,
formula)
data |
the data as a data frame |
var |
the variable of interest in |
counts |
the counts in |
expected |
|
ratio |
a vector of numbers: the expected proportions |
formula |
(optional) the formula to use, see the examples |
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)
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
# -----------------------
#
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