$np \ge 10$, where $n$ = sample size and $p$ = probability of success.

$n(1-p) \ge 10$, where $n$ = sample size and $p$ = probability of success.

$z = \frac{\hat{p} - p}{\sqrt{\frac{p(1-p)}{n}}}$

$\hat{p} = \frac{x}{n}$ where $x$ is the number of successes and $n$ is the sample size.

Data values scattered without a discernible pattern, often seen in random samples.

Indicates an underlying pattern or structure in the data, resulting from measurement error, bias or systematic differences.

A symmetrical, bell-shaped curve used extensively in statistical inference.

Both expected successes ($np$) and expected failures ($n(1-p)$) must be at least 10.

A measure of how many standard deviations a data point is from the mean.

Random: No discernible pattern, pure chance | Non-random: Underlying pattern, due to measurement error/bias.

Successes: $np \ge 10$, expected number of successes is at least 10 | Failures: $n(1-p) \ge 10$, expected number of failures is at least 10.