You have sample data that leads you to believe that the average high temperature in Oklahoma City is \( 92^{\circ} \mathrm{F} \). What is the alternative hypothesis, \( H_{a} \), for this situation? \( \mu<90 \) \( \mu>90 \) \( \mu=90 \) \( \mu \neq 90 \)

In hypothesis testing, the alternative hypothesis \( H_a \) represents a statement that contradicts the null hypothesis \( H_0 \). In this case, the null hypothesis would typically state that the average high temperature in Oklahoma City is equal to a specific value, which we can assume to be \( 90^{\circ} \mathrm{F} \) based on the options provided. Given that the average high temperature is believed to be \( 92^{\circ} \mathrm{F} \), the alternative hypothesis would suggest that the average temperature is not equal to \( 90^{\circ} \mathrm{F} \). Thus, the correct alternative hypothesis \( H_a \) for this situation is: \[ H_a: \mu \neq 90 \] This indicates that the average high temperature is significantly different from \( 90^{\circ} \mathrm{F} \).