A meteorologist claims that the average daily high temperature in Oklahoma City is \( 90^{\circ} \mathrm{F} \). Let \( \mu \) represent the average daily high temperature, in \( { }^{\circ} \mathrm{F} \), in Oklahoma City during the summer. What is the null hypothesis, \( H_{0} \), for this situation? \( \mu<90 \) \( \mu=90 \) \( \mu>90 \) \( \mu \geq 90 \) DONE

The null hypothesis, \( H_{0} \), is typically a statement of no effect or no difference, and in this case, it serves as a baseline to compare against. Therefore, the correct null hypothesis here would be that the average daily high temperature in Oklahoma City is exactly \( 90^{\circ} \mathrm{F} \), denoted as \( H_{0}: \mu = 90 \). In hypothesis testing, rejecting the null hypothesis suggests that there is sufficient statistical evidence to support an alternative claim. Remember, the null hypothesis assumes that any variation observed is due to chance. So, if scientists find evidence otherwise, it could lead to some exciting discoveries about weather patterns!