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.

This exercise is part of the course

Inference for Categorical Data in R

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Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Generate null distribution
___ <- gss2016 %>%
  specify(response = postlife, success = "YES") %>%
  hypothesize(null = "point", p = 0.75) %>%
  generate(reps = ___, type = "simulate") %>%
  # Calculate proportions
  ___(stat = ___)

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