Proportion Estimation: Difference between revisions

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Proportion estimation is another common task for sample statistics.


<math>
\hat{p} = \frac{y}{n}
</math>
where <math>y</math> is the number of subjects in the sample with a
particular trait, and <math>n</math> is the sample size.
We have
<math>
\mu_\hat{p} = p, \sigma_\hat{p} = \sqrt{\frac{p (1 - p)}{n}}
</math>
and standard error
<math>
SE = \sqrt{\frac{\hat{p} (1 - \hat{p})}{n}}
</math>
[[Category:Sample Statistics]]

Revision as of 01:58, 16 March 2024

Proportion estimation is another common task for sample statistics.

Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \hat{p} = \frac{y}{n} }

where is the number of subjects in the sample with a particular trait, and Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle n} is the sample size.

We have

Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \mu_\hat{p} = p, \sigma_\hat{p} = \sqrt{\frac{p (1 - p)}{n}} }

and standard error

Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle SE = \sqrt{\frac{\hat{p} (1 - \hat{p})}{n}} }