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? $$ \mu90 $$ $$ \mu=90 $$ $$ \mu eq 90 $$ DONE

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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? $$ \mu<90 $$ $$ \mu>90 $$ $$ \mu=90 $$ $$ \mu 
eq 90 $$ DONE

UpStudy AI · Accepted Answer

In hypothesis testing, the alternative hypothesis $$ H_a $$ represents what we are trying to find evidence for, while the null hypothesis $$ H_0 $$ represents a statement of no effect or no difference.

Given that the average high temperature in Oklahoma City is believed to be $$ 92^{\circ} \mathrm{F} $$, we can set up the hypotheses as follows:

1. **Null Hypothesis $$ H_0 $$**: The average high temperature is $$ 90^{\circ} \mathrm{F} $$ (or any value that we are testing against).
   - $$ H_0: \mu = 90 $$

2. **Alternative Hypothesis $$ H_a $$**: This is what we are testing for. Since we are interested in whether the average high temperature is different from $$ 90^{\circ} \mathrm{F} $$, the alternative hypothesis would be:
   - $$ H_a: \mu 
eq 90 $$

Thus, the correct alternative hypothesis for this situation is:

$$ H_a: \mu 
eq 90 $$
The alternative hypothesis $$ H_a $$ is $$ \mu 
eq 90 $$.

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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