Proportion Test (N Outcomes)
The χ² Goodness of fit test (not to be confused with the χ² 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.
Example usage
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
# ────────────────────────────────
#
#
# χ² Goodness of Fit
# ───────────────────────
# χ² df p
# ───────────────────────
# 133 3 < .001
# ───────────────────────
#
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 |
Returns
A results object containing:
| results$props | a table |
| results$tests | a table |
Tables can be converted to data frames with asDF or as.data.frame(). For example:
results$props$asDF
as.data.frame(results$props)