(c) Carry out a formal test of the hypotheses suggested in part (b). Find the test statistic and Pvalue. (Use a- 0.05. Round your test statistic to two decimal places and your P.value to four decimal places.) P.value

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**Use Salt: Analyzing Calorie Content of Packaged Goods**

Many consumers pay careful attention to stated nutritional contents on packaged foods when making purchases. It is essential that the information on packages be accurate. A random sample of \( n = 12 \) frozen dinners of a certain type was selected from production during a particular period, and the calorie content of each was determined. (This determination entails destroying the product, so a census would certainly not be desirable!) Here are the resulting observations, along with a boxplot and normal probability plot. (Use [this dataset](#) for your analysis software.)

Observations (Calories):  
255, 244, 239, 242, 265, 245, 259, 248, 225, 226, 251, 233

**Diagrams:**

1. **Boxplot**  
   - A horizontal boxplot showing calorie contents ranging from approximately 220 to 270.
   - The box stretches from about 231 to 259, with the median line near 244.
   - A slight outlier at 265.

2. **Normal Probability Plot**  
   - A scatter plot of normal scores versus calories.
   - Most points follow a roughly linear trend line, with some deviations at the extremes.

### (a) Is it reasonable to test hypotheses about mean calorie content by using a t-test? Explain why or why not.

- **Yes, it is reasonable.** The pattern in the normal probability plot is roughly linear, and since the sample was a random sample from the population, the t-test is appropriate.  
- No, a t-test is not applicable here. The pattern in the normal probability plot is not roughly linear. Therefore, the t-test is not appropriate.  
- It depends on the results of the test.

### (b) The stated calorie content is 243. Does the boxplot suggest that true average content differs from the stated value? Explain your reasoning.

- **Yes**, the center of the boxplot is different from the stated value indicating the true average content must differ from the stated value.  
- No, not necessarily. It is possible the true average content is 243 and observed differences could be due to sampling variability.

### (c) Carry out a formal test of the hypotheses suggested in part (b).

Find the test statistic and P-value. (Use \( \alpha = 0.05 \). Round your test statistic to two
Transcribed Image Text:**Use Salt: Analyzing Calorie Content of Packaged Goods** Many consumers pay careful attention to stated nutritional contents on packaged foods when making purchases. It is essential that the information on packages be accurate. A random sample of \( n = 12 \) frozen dinners of a certain type was selected from production during a particular period, and the calorie content of each was determined. (This determination entails destroying the product, so a census would certainly not be desirable!) Here are the resulting observations, along with a boxplot and normal probability plot. (Use [this dataset](#) for your analysis software.) Observations (Calories): 255, 244, 239, 242, 265, 245, 259, 248, 225, 226, 251, 233 **Diagrams:** 1. **Boxplot** - A horizontal boxplot showing calorie contents ranging from approximately 220 to 270. - The box stretches from about 231 to 259, with the median line near 244. - A slight outlier at 265. 2. **Normal Probability Plot** - A scatter plot of normal scores versus calories. - Most points follow a roughly linear trend line, with some deviations at the extremes. ### (a) Is it reasonable to test hypotheses about mean calorie content by using a t-test? Explain why or why not. - **Yes, it is reasonable.** The pattern in the normal probability plot is roughly linear, and since the sample was a random sample from the population, the t-test is appropriate. - No, a t-test is not applicable here. The pattern in the normal probability plot is not roughly linear. Therefore, the t-test is not appropriate. - It depends on the results of the test. ### (b) The stated calorie content is 243. Does the boxplot suggest that true average content differs from the stated value? Explain your reasoning. - **Yes**, the center of the boxplot is different from the stated value indicating the true average content must differ from the stated value. - No, not necessarily. It is possible the true average content is 243 and observed differences could be due to sampling variability. ### (c) Carry out a formal test of the hypotheses suggested in part (b). Find the test statistic and P-value. (Use \( \alpha = 0.05 \). Round your test statistic to two
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