Suppose that there were no previous studies in the medical literature indicating that the population distributio the differences in blood viscocity follows a normal distribution. Then the researchers would not be able to assume the data follow a normal distribution. Thus, researchers created the normal probability plot (shown below) for this study. Which test should be used based on the normal probability plot? OA. Two Sample t Test OB. Paired Sample t Test OC. Wilcoxon-Mann-Whitney Test O D. Sign Test OE. Binomial Test for p OF. Chi-Square Goodness-of-Fit Test OG. None of the above
Suppose that there were no previous studies in the medical literature indicating that the population distributio the differences in blood viscocity follows a normal distribution. Then the researchers would not be able to assume the data follow a normal distribution. Thus, researchers created the normal probability plot (shown below) for this study. Which test should be used based on the normal probability plot? OA. Two Sample t Test OB. Paired Sample t Test OC. Wilcoxon-Mann-Whitney Test O D. Sign Test OE. Binomial Test for p OF. Chi-Square Goodness-of-Fit Test OG. None of the above
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
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Transcribed Image Text:**Educational Content: Understanding Normal Probability Plots in Blood Viscosity Studies**
In research, it is crucial to determine whether the data follow a normal distribution, especially when no prior studies exist. This scenario explores the distribution of differences in blood viscosity, where a normal probability plot is used to guide the choice of statistical test.
**Normal Probability Plot:**
- A graphical technique used to assess if a dataset is approximately normally distributed.
- Data points forming a straight line suggest a normal distribution; deviations from the line indicate non-normality.
**Given Scenario:**
Researchers have constructed a normal probability plot (displayed above) to analyze blood viscosity differences. The lack of alignment with a straight line suggests the data may not be normally distributed.
**Choosing the Appropriate Test:**
1. **Two Sample t Test**
2. **Paired Sample t Test**
3. **Wilcoxon-Mann-Whitney Test**: A non-parametric test for differences between two independent samples.
4. **Sign Test**: A non-parametric test for matched or paired data.
5. **Binomial Test for p**
6. **Chi-Square Goodness-of-Fit Test**
7. **None of the above**
**Conclusion:**
Based on the plot's indication of non-normality, non-parametric tests like the Wilcoxon-Mann-Whitney Test (C) or the Sign Test (D) might be more suitable, rather than tests assuming normality such as the t-tests (A and B).

Transcribed Image Text:### Study on the Effects of Xarelto on Blood Viscosity
Xarelto is a drug used as a blood thinner for patients with pulmonary embolism or other blood clotting conditions. Researchers conducted a study to assess if there is a change in blood viscosity (measured in mPA·S) after treatment with Xarelto. Seven patients with a familial history of blood clotting disorders were treated with the drug for two months. The viscosity of their blood was recorded both before and after treatment, as shown in the table below:
| Patient | Before | After | Difference = After - Before |
|---------|--------|-------|-----------------------------|
| 1 | 6.7 | 4.3 | -2.4 |
| 2 | 7.1 | 4.6 | -2.5 |
| 3 | 5.6 | 6.7 | 1.1 |
| 4 | 6.9 | 4.4 | -2.5 |
| 5 | 7.5 | 6.0 | -1.5 |
| 6 | 6.8 | 4.9 | -1.9 |
| 7 | 5.7 | 5.8 | 0.1 |
| **Mean (
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Given that, Xarelto is a drug that can be used as a blood thinner for patients who have a pulmonary embolism or other blood clotting condition. Researchers wanted to determine if there was a difference in blood viscosity (measured in mPAS) that might be attributed to the drug. In a study, a random sample of 7 patients who had a family history of blood clotting disorders were treated with Xarelto for two months. Their blood viscosity was measured before and after the treatment.
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