Standard Error of the Proportion Calculator
Calculate the standard error of a sample proportion.
Understanding the Standard Error of the Proportion
The standard error of the proportion estimates how much a sample proportion \( \hat{p} \) would vary if multiple samples were drawn from the same population. It’s used to construct confidence intervals and test hypotheses about proportions.
Formula for Standard Error of the Proportion
The standard error \( SE \) is calculated using the following formula:
$$ SE = \sqrt{\frac{\hat{p} (1 - \hat{p})}{n}} $$
where:
- \( \hat{p} \): Sample proportion
- \( n \): Sample size
Example Calculation
Suppose a survey finds that 60% of respondents support a new policy. With a sample size of 150, the standard error is calculated as follows:
- Step 1: Set \( \hat{p} = 0.6 \) and \( n = 150 \).
- Step 2: Substitute values into the formula: \[ SE = \sqrt{\frac{0.6 \times (1 - 0.6)}{150}} = 0.039 \]
This means the standard error of the proportion is approximately 0.039, giving an idea of the sampling variability.
Suf is a senior advisor in data science with deep expertise in Natural Language Processing, Complex Networks, and Anomaly Detection. Formerly a postdoctoral research fellow, he applied advanced physics techniques to tackle real-world, data-heavy industry challenges. Before that, he was a particle physicist at the ATLAS Experiment of the Large Hadron Collider. Now, he’s focused on bringing more fun and curiosity to the world of science and research online.