A paired difference experiment produced the data given below. Complete parts a through e below. na = 16 Xq = - 7 s3 = 25 X1 = 148 X2 = 155 a. Determine the values of t for which the null hypothesis p, -42 = 0 would be rejected in favor of the alternative hypothesis u, - H2 <0. Use a= 0.10. (Round to two decimal places as needed.) O A. The rejection region is t> O B. The rejection region is t< or t>. O C. The rejection region is

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### Paired Difference Experiment Analysis

In this example, a paired difference experiment is conducted, and the following data was collected:

- Number of pairs (\(n_d\)): 16
- Mean of the first sample (\(\bar{x}_1\)): 148
- Mean of the second sample (\(\bar{x}_2\)): 155
- Mean of the differences (\(\bar{x}_d\)): -7
- Variance of the differences (\(s_d^2\)): 25

#### Objective

The objective is to determine the values of the t-statistic for which the null hypothesis \( \mu_1 - \mu_2 = 0 \) would be rejected in favor of the alternative hypothesis \( \mu_1 - \mu_2 < 0 \), using a significance level (\(\alpha\)) of 0.10.

#### Steps and Options for Determining Rejection Regions

The options provided for the rejection region are:

**A.** The rejection region is \( t > \) [ ]  
**B.** The rejection region is \( t < \) [ ] or \( t > \) [ ]  
**C.** The rejection region is [ ] \( < t < \) [ ]  
**D.** The rejection region is \( t < \) [ ]

### Explanation of Graphs or Diagrams

In the provided snippet, there are no graphs or diagrams included. The focus is on statistical hypothesis testing using the provided sample data and determining the rejection region for the t-statistic. 

To determine the specific values for the t-statistic and complete the options, one would generally follow these steps:

1. **Calculate the test statistic:** This involves using the provided sample data to compute the test value.
2. **Determine the critical value:** Based on the significance level (\(\alpha = 0.10\)) and the degrees of freedom (which is \( n_d - 1 \) for a paired t-test), the critical value for the t-distribution can be found using statistical tables or software.
3. **Compare the test statistic to the critical value:** Decide which of the options matches the criterion for rejecting the null hypothesis.

This example illustrates key concepts in hypothesis testing, particularly about paired difference experiments and the use of the t-distribution in making statistical decisions.
Transcribed Image Text:### Paired Difference Experiment Analysis In this example, a paired difference experiment is conducted, and the following data was collected: - Number of pairs (\(n_d\)): 16 - Mean of the first sample (\(\bar{x}_1\)): 148 - Mean of the second sample (\(\bar{x}_2\)): 155 - Mean of the differences (\(\bar{x}_d\)): -7 - Variance of the differences (\(s_d^2\)): 25 #### Objective The objective is to determine the values of the t-statistic for which the null hypothesis \( \mu_1 - \mu_2 = 0 \) would be rejected in favor of the alternative hypothesis \( \mu_1 - \mu_2 < 0 \), using a significance level (\(\alpha\)) of 0.10. #### Steps and Options for Determining Rejection Regions The options provided for the rejection region are: **A.** The rejection region is \( t > \) [ ] **B.** The rejection region is \( t < \) [ ] or \( t > \) [ ] **C.** The rejection region is [ ] \( < t < \) [ ] **D.** The rejection region is \( t < \) [ ] ### Explanation of Graphs or Diagrams In the provided snippet, there are no graphs or diagrams included. The focus is on statistical hypothesis testing using the provided sample data and determining the rejection region for the t-statistic. To determine the specific values for the t-statistic and complete the options, one would generally follow these steps: 1. **Calculate the test statistic:** This involves using the provided sample data to compute the test value. 2. **Determine the critical value:** Based on the significance level (\(\alpha = 0.10\)) and the degrees of freedom (which is \( n_d - 1 \) for a paired t-test), the critical value for the t-distribution can be found using statistical tables or software. 3. **Compare the test statistic to the critical value:** Decide which of the options matches the criterion for rejecting the null hypothesis. This example illustrates key concepts in hypothesis testing, particularly about paired difference experiments and the use of the t-distribution in making statistical decisions.
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