Testing a claim
In the last exercise, you got a sense of what a single simulated p-hat might be if in fact the true proportion of believers was 0.75. That p-hat was likely different from the p-hat in gss2016, but was that a fluke or is there a systematic inconsistency between that claim and the data in the GSS?
In this exercise, you'll settle this question.
Cet exercice fait partie du cours
Inference for Categorical Data in R
Exercice interactif pratique
Essayez cet exercice en complétant cet exemple de code.
# Generate null distribution
___ <- gss2016 %>%
specify(response = postlife, success = "YES") %>%
hypothesize(null = "point", p = 0.75) %>%
generate(reps = ___, type = "simulate") %>%
# Calculate proportions
___(stat = ___)