Refer to the measured systolic and diastolic blood pressure measurements of 40 randomly selected males and test the claim that among men, there is a correlation between systolic blood pressure and diastolic blood pressure. Test for rank correlation with a 0.05 significance level. Click here to view the blood pressure data for men. Click here to view the critical values of Spearman's rank correlation coefficient. Systolic vs. Diastolic blood pressure Determine the null and alternative hypotheses for this test. Choose the correct answer below. OA Ho:r, 40 Blood Pressure Systolic Diastolic OB. Ho: Ps H: Pa Systolic Diastolic Systolic Diastolic o H:r, 0 133 79 131 83 134 84 OC. Ho:, 0 123 D. Ho: Ps 75 150 82 155 89 H:, 40 105 70 119 72 113 77 H: Ps 104 62 135 75 142 75 Determine the correlation coefficient. 123 82 160 88 116 66 r. (Round to three decimal places as needed.) 151 81 100 59 156 87 115 78 160 89 158 83 102 70 130 69 128 79 160 81 115 79 115 77 157 74 103 69 109 63 154 77 101 67 130 69 116 75 158 79 143 80 114 67 117 78 108 67 158 85

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PLEASE HELP ANSWER IS NOT 0.755 I NEED IN 15 minutes now please help I also need the critical values and conclusion 

**Spearman's Rank Correlation Coefficient**

The image displays a graph and a table related to Spearman's Rank Correlation Coefficient. 

### Graph Explanation
The graph is a symmetrical, bell-shaped curve depicting the distribution of Spearman's rank correlation coefficient (\( r_s \)). It ranges from -1 to 1, with critical regions shaded on both tails representing \(\alpha/2\) (the significance level divided by two). These shaded areas indicate where the critical values lie for determining the significance of the correlation.

### Table of Critical Values
The table lists the critical values of Spearman’s Rank Correlation Coefficient (\( r_s \)) for different sample sizes (\( n \)) and significance levels (\( \alpha \)). The values in the table allow you to determine if your calculated \( r_s \) is statistically significant.

| \( n \) | \( \alpha = 0.10 \) | \( \alpha = 0.05 \) | \( \alpha = 0.02 \) | \( \alpha = 0.01 \) |
|---------|-------------------|-------------------|-------------------|-------------------|
| 5       | .900            | —                 | —                 | —                 |
| 6       | .829            | .886              | .943              | —                 |
| 7       | .714            | .786              | .893              | .929              |
| 8       | .643            | .738              | .833              | .881              |
| 9       | .600            | .700              | .783              | .833              |
| 10      | .564            | .648              | .745              | .794              |
| 11      | .536            | .618              | .709              | .755              |

**Note:** A dash (“—”) means the critical value is not applicable or not calculated for that situation.

These critical values are crucial for hypothesis testing to determine if there is a statistically significant correlation between two ranked variables.
Transcribed Image Text:**Spearman's Rank Correlation Coefficient** The image displays a graph and a table related to Spearman's Rank Correlation Coefficient. ### Graph Explanation The graph is a symmetrical, bell-shaped curve depicting the distribution of Spearman's rank correlation coefficient (\( r_s \)). It ranges from -1 to 1, with critical regions shaded on both tails representing \(\alpha/2\) (the significance level divided by two). These shaded areas indicate where the critical values lie for determining the significance of the correlation. ### Table of Critical Values The table lists the critical values of Spearman’s Rank Correlation Coefficient (\( r_s \)) for different sample sizes (\( n \)) and significance levels (\( \alpha \)). The values in the table allow you to determine if your calculated \( r_s \) is statistically significant. | \( n \) | \( \alpha = 0.10 \) | \( \alpha = 0.05 \) | \( \alpha = 0.02 \) | \( \alpha = 0.01 \) | |---------|-------------------|-------------------|-------------------|-------------------| | 5 | .900 | — | — | — | | 6 | .829 | .886 | .943 | — | | 7 | .714 | .786 | .893 | .929 | | 8 | .643 | .738 | .833 | .881 | | 9 | .600 | .700 | .783 | .833 | | 10 | .564 | .648 | .745 | .794 | | 11 | .536 | .618 | .709 | .755 | **Note:** A dash (“—”) means the critical value is not applicable or not calculated for that situation. These critical values are crucial for hypothesis testing to determine if there is a statistically significant correlation between two ranked variables.
**Educational Resource: Analyzing Correlation Between Systolic and Diastolic Blood Pressure**

**Objective:**  
This exercise involves analyzing the relationship between systolic and diastolic blood pressure measurements from a sample of 40 randomly selected males. The goal is to test the claim of a correlation between these two variables using Spearman's rank correlation coefficient at a significance level of 0.05.

**Data Sources:**  
- [Blood pressure data for men](#)
- [Critical values of Spearman's rank correlation coefficient](#)

---

**Hypotheses:**  
Determine the null and alternative hypotheses for this test. Choose the correct answer below:

- A. \( H_0: r_s \neq 0 \), \( H_1: r_s = 0 \)
- B. \( H_0: r_s = 0 \), \( H_1: r_s = 0 \)
- C. \( H_0: r_s = 0 \), \( H_1: r_s \neq 0 \)

**Correct Answer:**  
- D. \( H_0: \rho_s = 0 \), \( H_1: \rho_s \neq 0 \)

**Task:**  
Determine the correlation coefficient.

\( r_s = \) \_\_\_ (Round to three decimal places as needed.)

---

**Blood Pressure Data Table:**

The data table is titled "Systolic vs. Diastolic Blood Pressure." It consists of paired measurements of systolic and diastolic blood pressure for 40 sample entries.

**Sample Data Points:**

- Systolic 133, Diastolic 79
- Systolic 123, Diastolic 75
- ...
- Systolic 114, Diastolic 69
- Systolic 108, Diastolic 67

This exercise illustrates the method of using real-world data to assess the relationship between two physiological parameters through statistical analysis, enhancing understanding of hypothesis testing and correlation calculation.
Transcribed Image Text:**Educational Resource: Analyzing Correlation Between Systolic and Diastolic Blood Pressure** **Objective:** This exercise involves analyzing the relationship between systolic and diastolic blood pressure measurements from a sample of 40 randomly selected males. The goal is to test the claim of a correlation between these two variables using Spearman's rank correlation coefficient at a significance level of 0.05. **Data Sources:** - [Blood pressure data for men](#) - [Critical values of Spearman's rank correlation coefficient](#) --- **Hypotheses:** Determine the null and alternative hypotheses for this test. Choose the correct answer below: - A. \( H_0: r_s \neq 0 \), \( H_1: r_s = 0 \) - B. \( H_0: r_s = 0 \), \( H_1: r_s = 0 \) - C. \( H_0: r_s = 0 \), \( H_1: r_s \neq 0 \) **Correct Answer:** - D. \( H_0: \rho_s = 0 \), \( H_1: \rho_s \neq 0 \) **Task:** Determine the correlation coefficient. \( r_s = \) \_\_\_ (Round to three decimal places as needed.) --- **Blood Pressure Data Table:** The data table is titled "Systolic vs. Diastolic Blood Pressure." It consists of paired measurements of systolic and diastolic blood pressure for 40 sample entries. **Sample Data Points:** - Systolic 133, Diastolic 79 - Systolic 123, Diastolic 75 - ... - Systolic 114, Diastolic 69 - Systolic 108, Diastolic 67 This exercise illustrates the method of using real-world data to assess the relationship between two physiological parameters through statistical analysis, enhancing understanding of hypothesis testing and correlation calculation.
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