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  3. Inference for Categorical Data in R

Exercise

CI via approximation

The approximation shortcut offers an alternative method of describing the sampling distribution. In this exercise, you will apply the approximation shortcut to build a confidence interval for the proportion of respondents that live in the pacific region.

When building any confidence interval, note that you use three ingredients: the point estimate (here, p_hat), the SE, and the number of standard errors to add and subtract. For a sampling distribution that is bell-shaped, adding and subtracting two SEs corresponds to a confidence level of 95%. When you use the bootstrap, you can check that the distribution is bell-shaped because you have a have the bootstrap distribution to plot. When you use the approximation, you're flying blind — well, not quite blind, but you are dependent on the "rule of thumb" to ensure that you're working with a bell shape.

Instructions 1/2

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  • Calculate the sample size, n (which is the number of rows).
  • Calculated the observed statistic, p_hat, as the proportion of people in the "pacific" meta-region.