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? \( \mu<90 \) \( \mu>90 \) \( \mu=90 \) \( \mu \neq 90 \) DONE
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Extra Insights
If your sample data suggests that the average high temperature in Oklahoma City is 92°F, the alternative hypothesis, \( H_{a} \), would be \( \mu \neq 90 \). This hypothesis indicates that the average high temperature is not equal to 90°F, which is the value you might be testing against. Essentially, you're asserting that the true average temperature differs from 90°F, possibly being higher based on your observation. In hypothesis testing, it's crucial to differentiate between the null hypothesis, which often posits that there's no difference (in this case, that the average is 90°F), and the alternative hypothesis, which suggests a difference exists. So, you’re on the correct track in thinking there's a need for exploration beyond that single number!