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To analyze this hypothesis testing question:

### Problem Breakdown:
The **claim** is that the new sedan, the Libra, will average **better than 32 miles per gallon**.  
- This means the **alternative hypothesis (\(H_1\))** would test whether the mean mileage, \(\mu\), is **greater than 32**.
- The **null hypothesis (\(H_0\))** is the opposite of this claim, stating that \(\mu\) is **less than or equal to 32**.

### Correct Answer:
The hypotheses are:
- **\(H_0: \mu \leq 32\)** (the car does not average better than 32 mpg)
- **\(H_1: \mu > 32\)** (the car averages better than 32 mpg)

Thus, the correct choice is **C**:
- \(H_0: \mu \leq 32\)
- \(H_1: \mu > 32\)

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Do you need additional details or help with hypothesis testing steps?  
Here are 5 related questions you might explore:  
1. How do you determine the rejection region for a one-tailed test like this?  
2. What is the role of the significance level (\(\alpha\)) in hypothesis testing?  
3. What test statistic would you use for this scenario?  
4. How does sample size affect the validity of hypothesis testing?  
5. When should you use a one-tailed test versus a two-tailed test?  

**Tip:** Always align the alternative hypothesis with the claim being tested to ensure clarity.

Carter Motor Company claims that its new sedan, the Libra, will average better than 32 miles per gallon in the city. Use μ, the true average mileage of the Libra.

Understand the null and alternative hypotheses for Carter Motor Company's claim that their new sedan averages better than 32 MPG in the city. Learn the basics of hypothesis testing, including one-tailed tests and statistical means. Suitable for college-level statistics students.

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