- In practice, we may trust this test when the number of successes is $10$ or greater and the number of failures is $10$ or greater. That is, when $np_0 \geq 10$ and $n(1 - p_0) \geq 10$.
- When the above guidelines for this test are not met, you may use a non-parametric alternative: Bootstrap Test for a Single Population Proportion.
| Number of Successes | Sample Size | |
| Sample Data: | $k=$ | $n=$ |
| Null Hypothesis: | $H_0: p=p_0=$ | |
| Alternative Hypothesis: | $H_a:p$ $p_0$ | |
| Significance Level: | $\alpha=$ |
| Sample Size: | $n=$ |
| Sample Proportion: | $\hat{p}=$ |
| Standard Error: | $\mbox{SE}_{\hat{p}}=$ |
| Critical $z$ Value: | $z^{*}=$ |
| $z$ Statistic: | $z=$ |
| $p\mbox{-value}$: | $p\mbox{-value}=$ |