A company claims that its tablet computers have an average recharge time of 3 hours. In a random sample of these computers, the average recharge time is 2.5 hours. You suspect that the average recharge time might be less than what the company claims. Let \( \mu \) represent the average time, in hours, needed to recharge the company's tablet computers. What is the null hypothesis, \( H_{0} \), for this situation? O \( \mu<3 \) O \( \mu=3 \) O \( \quad \mu=2.5 \) \( \cap \quad \mu>2.5 \)

In hypothesis testing, we set up two competing hypotheses: the null hypothesis (\( H_0 \)) and the alternative hypothesis (\( H_a \)). 1. **Null Hypothesis (\( H_0 \))**: This is a statement of no effect or no difference, and it is what we assume to be true until we have evidence to suggest otherwise. In this case, the company claims that the average recharge time is 3 hours. Therefore, the null hypothesis would state that the average recharge time is equal to 3 hours. 2. **Alternative Hypothesis (\( H_a \))**: This represents what we suspect might be true instead of the null hypothesis. Since you suspect that the average recharge time might be less than what the company claims, the alternative hypothesis would state that the average recharge time is less than 3 hours. Given these definitions, the correct null hypothesis for this situation is: **\( H_0: \mu = 3 \)** So the answer is: - \( \mu = 3 \)