Data on the weights (Ib) of the contents of cans of diet soda versus the contents of cans of the regular version of the soda is summarized to the right Assume that the two samples are independent simple random samples selected from normally distributed populations, and do not assume that the population standard deviations are equal. Complete parts (a) and (b) below. Use a 0.01 significance level for both parts. Diet Regular 27 0.79037 Ib 0.00449 lb 27 0.80399 Ib 0.00756 lb a. Test the claim that the contents of cans of diet soda have weights with a mean that is less than the mean for the regular soda. What are the null and alternative hypotheses? OA Hoi H" P2 H: H2 H 2 HHP2 The test statistic, t, is -8.04. (Round to two decimal places as needed.) The P-value is (Round to three decimal places as needed.)

MATLAB: An Introduction with Applications
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Author:Amos Gilat
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Chapter1: Starting With Matlab
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**Transcription and Explanation:**

The image presents a statistical analysis comparing the weights of diet and regular soda cans. Here is a transcription and explanation suitable for an educational website.

**Background:**
The study considers data on the contents of soda cans, comparing the weights of diet soda against regular soda. It is assumed that the samples are independent, normally distributed, and do not assume equal population standard deviations. The significance level is set at 0.01.

**Data Table Explanation:**
The table summarizes the data for diet and regular sodas:

|                  | Diet                     | Regular                    |
|------------------|--------------------------|----------------------------|
| Mean (\(\mu\))   | \(\mu_1\)                | \(\mu_2\)                  |
| Sample Size (n)  | 27                       | 27                         |
| Mean (x̄)         | 0.79037 lb               | 0.80399 lb                 |
| Std Dev (s)      | 0.00449 lb               | 0.00756 lb                 |

**Hypothesis Test:**
The objective is to test if the mean weight of diet soda cans is less than that of regular soda cans.

- **Null Hypothesis (\(H_0\)): \(\mu_1 = \mu_2\)** 
- **Alternative Hypothesis (\(H_1\)): \(\mu_1 < \mu_2\)** (Correct hypothesis choice as marked.)

**Test Statistic:**
The test statistic calculated is \(t = -8.04\). This value is rounded to two decimal places.

**P-value:**
The space for the P-value is prepared to be entered, which should be rounded to three decimal places, but it is not filled in the image.

This setup is typical of hypothesis testing scenarios where conclusions about population parameters are drawn from sample data under specific assumptions.
Transcribed Image Text:**Transcription and Explanation:** The image presents a statistical analysis comparing the weights of diet and regular soda cans. Here is a transcription and explanation suitable for an educational website. **Background:** The study considers data on the contents of soda cans, comparing the weights of diet soda against regular soda. It is assumed that the samples are independent, normally distributed, and do not assume equal population standard deviations. The significance level is set at 0.01. **Data Table Explanation:** The table summarizes the data for diet and regular sodas: | | Diet | Regular | |------------------|--------------------------|----------------------------| | Mean (\(\mu\)) | \(\mu_1\) | \(\mu_2\) | | Sample Size (n) | 27 | 27 | | Mean (x̄) | 0.79037 lb | 0.80399 lb | | Std Dev (s) | 0.00449 lb | 0.00756 lb | **Hypothesis Test:** The objective is to test if the mean weight of diet soda cans is less than that of regular soda cans. - **Null Hypothesis (\(H_0\)): \(\mu_1 = \mu_2\)** - **Alternative Hypothesis (\(H_1\)): \(\mu_1 < \mu_2\)** (Correct hypothesis choice as marked.) **Test Statistic:** The test statistic calculated is \(t = -8.04\). This value is rounded to two decimal places. **P-value:** The space for the P-value is prepared to be entered, which should be rounded to three decimal places, but it is not filled in the image. This setup is typical of hypothesis testing scenarios where conclusions about population parameters are drawn from sample data under specific assumptions.
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