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| Proportion estimation is another common task for sample statistics.
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| We have sample proportion
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| <math>
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| \hat{p} = \frac{y}{n}
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| </math>
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| where <math>y</math> is the number of subjects in the sample with a
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| particular trait, and <math>n</math> is the sample size.
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| We have
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| <math>
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| \mu_\hat{p} = p, \sigma_\hat{p} = \sqrt{\frac{p (1 - p)}{n}}
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| </math>
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| and standard error
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| <math>
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| SE = \sqrt{\frac{\hat{p} (1 - \hat{p})}{n}}
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| </math>
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| = Wilson-Adjusted CI for p =
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| ''Correcting'' the sample proportion narrows the confidence interval. We
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| do this with the '''Wilson-Adjusted estimate''' for <math>p</math>
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| <math>
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| \widetilde{p}
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| </math>
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| [[Category:Sample Statistics]]
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