What are the correct hypotheses? (Select the correct symbols and use decimal values not percentages.) Ho: | Select an answer || ? +J| Select an answer H1:| Select an answer || ? +| Select an answer + Original Claim = Select an answer df = Based on the hypotheses, find the following: Test Statistic = (Round to three decimal places.) Critical value(s) = (Round to three decimal places.) Shade the sampling distribution curve with the correct critical value(s) and shade the critical regions. The arrows can only be dragged to t-scores that are accurate to 1 place after the decimal point (these values correspond to the tick marks on the horizontal axis). Select from the drop down menu to shade to the left, to the right, between or left and right of the t-score(s). Shade: Left of a value +). Click and drag the arrows to adjust the values. -4 -1 4 -1.5 Decision: Select an answer Conclusion: Select an answer + the claim that the mpg on desert roads is better than in the mountains.

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### Do campers with trailers really get better mileage per gallon on the highway?

The table shows results from a study of the MPG (miles per gallon) of campers with trailers both in the mountains and on desert roads. Assume that the two samples are randomly selected, independent, the population standard deviations are not known and not considered equal. At the 0.05 significance level, test the claim that the mpg on desert roads is better than in the mountains.

#### MPG on Desert Roads
```
31.4  29.6  29.2  29.8
30.8  27.5  30.7  25.8
28.4  34.8  35.7
```

#### MPG in the Mountains
```
26.3  26.2  24.8  26.3
25.3  24.4  23.3  26.0
24.5
```

### Hypotheses:
What are the correct hypotheses? (Select the correct symbols and use decimal values, not percentages.)

- \( H_0 \) (Null Hypothesis): \( \mu_D \) (Desert) Select an answer \( \le = \ge \neq \) \( \mu_M \) (Mountains)
- \( H_1 \) (Alternative Hypothesis): \( \mu_D \) (Desert) Select an answer \( \le = \ge \neq \) \( \mu_M \) (Mountains)
- Original Claim: Select an answer \( H_0 \) \( H_1 \)

\( df = \quad \)

### Calculations:
Based on the hypotheses, find the following:
- Test Statistic = \_\_\_\_ (Round to three decimal places.)
- Critical value(s) = \_\_\_\_ (Round to three decimal places.)

### Sampling Distribution Curve:
Shade the sampling distribution curve with the correct critical value(s) and shade the critical regions. The arrows can only be dragged to t-scores that are accurate to 1 place after the decimal point (these values correspond to the tick marks on the horizontal axis). Select from the drop-down menu to shade to the left, to the right, between or left and right of the t-score(s).

- Shade: \( \text{Select an answer} \boxed{\text{Left of a value}} \boxed
Transcribed Image Text:### Do campers with trailers really get better mileage per gallon on the highway? The table shows results from a study of the MPG (miles per gallon) of campers with trailers both in the mountains and on desert roads. Assume that the two samples are randomly selected, independent, the population standard deviations are not known and not considered equal. At the 0.05 significance level, test the claim that the mpg on desert roads is better than in the mountains. #### MPG on Desert Roads ``` 31.4 29.6 29.2 29.8 30.8 27.5 30.7 25.8 28.4 34.8 35.7 ``` #### MPG in the Mountains ``` 26.3 26.2 24.8 26.3 25.3 24.4 23.3 26.0 24.5 ``` ### Hypotheses: What are the correct hypotheses? (Select the correct symbols and use decimal values, not percentages.) - \( H_0 \) (Null Hypothesis): \( \mu_D \) (Desert) Select an answer \( \le = \ge \neq \) \( \mu_M \) (Mountains) - \( H_1 \) (Alternative Hypothesis): \( \mu_D \) (Desert) Select an answer \( \le = \ge \neq \) \( \mu_M \) (Mountains) - Original Claim: Select an answer \( H_0 \) \( H_1 \) \( df = \quad \) ### Calculations: Based on the hypotheses, find the following: - Test Statistic = \_\_\_\_ (Round to three decimal places.) - Critical value(s) = \_\_\_\_ (Round to three decimal places.) ### Sampling Distribution Curve: Shade the sampling distribution curve with the correct critical value(s) and shade the critical regions. The arrows can only be dragged to t-scores that are accurate to 1 place after the decimal point (these values correspond to the tick marks on the horizontal axis). Select from the drop-down menu to shade to the left, to the right, between or left and right of the t-score(s). - Shade: \( \text{Select an answer} \boxed{\text{Left of a value}} \boxed
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