Proportion Test (N Outcomes)
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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