Explanation

In hypothesis testing, the alternative hypothesis represents the 'suspected' or 'hoped for' condition. Here, the goal is to test whether the population mean (μ) is greater than zero. Therefore, the alternative hypothesis should reflect this condition as μ > 0.

• Option A (μ ≤ 0): Incorrect because this represents the null hypothesis, not the alternative. The null hypothesis typically includes the equality condition (μ = 0) and is the statement we test against.
• Option B (μ ≥ 0): Incorrect because the 'suspected' condition is specifically μ > 0, not a broader condition like μ ≥ 0.
• Option C (μ > 0): Correct because it directly aligns with the 'suspected' condition and serves as the appropriate alternative hypothesis.

Hypothesis testing involves evaluating the null hypothesis at the point of equality (μ = 0) and seeking evidence to support the alternative hypothesis (μ > 0). This framework ensures clarity in statistical inference and decision-making.