Answer: (ii) Rejecting null when true

Explanation — Hypothesis Testing Errors:

Let $H_0$ = null hypothesis.

• Type I Error ($\alpha$): False Positive — reject $H_0$ when $H_0$ is actually true. $P(\text{Type I}) = \alpha$ (significance level, e.g., 0.05). Example: Convicting an innocent person.
• Type II Error ($\beta$): False Negative — accept / fail to reject $H_0$ when $H_1$ is true (i.e., $H_0$ false). $P(\text{Type II}) = \beta$, Power $=1-\beta$. Example: Acquitting a guilty person.
• (i) Accepting null when false → Type II
• (ii) Rejecting null when true → Type I ✓
• Confusion matrix mapping: Type I = FP, Type II = FN.

Hence (ii) correct.