$z = \frac{\hat{p} - p_0}{\sqrt{\frac{p_0(1-p_0)}{n}}}$ where $\hat{p}$ is the sample proportion, $p_0$ is the hypothesized population proportion, and n is the sample size.

$\sqrt{\frac{p_0(1-p_0)}{n}}$ where $p_0$ is the hypothesized population proportion, and n is the sample size.

Null Hypothesis: Statement we are trying to find evidence against, assumes no effect. | Alternative Hypothesis: Statement we are trying to support, contradicts the null hypothesis.

One-tailed Test: Tests for a change in one direction (either > or <). | Two-tailed Test: Tests for a change in either direction (≠).

The statement we're trying to find evidence against. It's our initial assumption about the population parameter, written as p = [some value].

The claim that contradicts the null hypothesis, written as p < [some value], p > [some value], or p ≠ [some value].

A test where the alternative hypothesis uses < or >, indicating interest in a change in one direction only.

A test where the alternative hypothesis uses ≠, indicating interest in a change in either direction.

The probability of getting a sample proportion as extreme as (or more extreme than) ours, assuming the null hypothesis is true.