coronavirus and patients' blood type. The population in Wuhan has a blood type distribution as shown in the table below. The researchers categorized Snsamp patients who had contracted coronavirus by blood type. Round all calculated values in this problem to 4 decimal places. Blood Type Population Percentage COVID-19 patients Туре А 33% 115 Туре В 24% 101 Туре АВ 9% 41 Туре О 34% 118 Total 100% 375 1. Enter the expected values for the hypothesis test in the table below: Blood Type Expected Value Type A Туре В Type AB Туре О 2. The researchers wonder if, in Wuhan, COVID-19 patients have a different distribution of blood type than the general population of Wuhan. Express this research question in terms of a null and alternative hypothesis. Ho: The distribution of blood type of COVID-19 patients is the same as the population. Any observed difference is not v due to chance. HA: The distribution of blood type of COVID-19 patients is different from v the population. Any observed difference is due to
coronavirus and patients' blood type. The population in Wuhan has a blood type distribution as shown in the table below. The researchers categorized Snsamp patients who had contracted coronavirus by blood type. Round all calculated values in this problem to 4 decimal places. Blood Type Population Percentage COVID-19 patients Туре А 33% 115 Туре В 24% 101 Туре АВ 9% 41 Туре О 34% 118 Total 100% 375 1. Enter the expected values for the hypothesis test in the table below: Blood Type Expected Value Type A Туре В Type AB Туре О 2. The researchers wonder if, in Wuhan, COVID-19 patients have a different distribution of blood type than the general population of Wuhan. Express this research question in terms of a null and alternative hypothesis. Ho: The distribution of blood type of COVID-19 patients is the same as the population. Any observed difference is not v due to chance. HA: The distribution of blood type of COVID-19 patients is different from v the population. Any observed difference is due to
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
Transcribed Image Text:### Blood type and COVID-19 susceptibility
A group of researchers in Wuhan, China investigated the relationship between contracting the novel coronavirus and patients’ blood type. The population in Wuhan has a blood type distribution as shown in the table below. The researchers categorized 375 patients who had contracted coronavirus by blood type.
Round all calculated values in this problem to 4 decimal places.
#### Blood Type Distribution in Wuhan Population and COVID-19 Patients
| Blood Type | Population Percentage | COVID-19 patients |
|------------|-----------------------|-------------------|
| Type A | 33% | 115 |
| Type B | 24% | 101 |
| Type AB | 9% | 41 |
| Type O | 34% | 118 |
| **Total** | **100%** | **375** |
**1. Enter the expected values for the hypothesis test in the table below:**
| Blood Type | Expected Value |
|------------|----------------|
| Type A | |
| Type B | |
| Type AB | |
| Type O | |
**2. The researchers wonder if, in Wuhan, COVID-19 patients have a different distribution of blood type than the general population of Wuhan. Express this research question in terms of a null and alternative hypothesis.**
**Null Hypothesis (H₀):** The distribution of blood type of COVID-19 patients is **the same as** the population. Any observed difference **is not** due to chance.
**Alternative Hypothesis (H₁):** The distribution of blood type of COVID-19 patients is **different from** the population. Any observed difference **is** due to chance.
![**Chi-Square Test for Blood Type Distribution in COVID-19 Patients**
**Objective:**
To determine if the distribution of blood types among COVID-19 patients in Wuhan is different from that of the general population.
**Procedure:**
2. **Hypothesis Formulation:**
- Null Hypothesis (\( H_0 \)): The distribution of blood type of COVID-19 patients is the same as the population. Any observed difference is not due to chance.
- Alternative Hypothesis (\( H_A \)): The distribution of blood type of COVID-19 patients is different from the population. Any observed difference is due to chance.
3. **Primary Variable Contribution:**
- Identify which blood type (A or O) contributes more to the test statistic.
- Options:
- A. type A
- B. type O
4. **Calculate the Test Statistic:**
- Chi-square test statistic (\( \chi^2 \)) calculation input field.
- \( \chi^2 = \) [Input Field]
5. **Degrees of Freedom:**
- State the degrees of freedom for this test.
- \( df = \) [Input Field]
6. **Calculate the p-value:**
- Input field to calculate the p-value for this test.
- \( p = \) [Input Field]
7. **Result Interpretation:**
- Based on the above p-value, select the strength of evidence against the null hypothesis.
- Options:
- [Dropdown] Strong evidence
This set of data aids in understanding how to apply statistical methods to compare categorical data distributions, specifically using chi-square tests to evaluate observed vs. expected frequency distributions.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F9a233757-ff48-478f-9071-7d7d23b994ff%2Faf70effb-f029-4297-8a22-d44a2c9e6783%2Fvky52go_processed.png&w=3840&q=75)
Transcribed Image Text:**Chi-Square Test for Blood Type Distribution in COVID-19 Patients**
**Objective:**
To determine if the distribution of blood types among COVID-19 patients in Wuhan is different from that of the general population.
**Procedure:**
2. **Hypothesis Formulation:**
- Null Hypothesis (\( H_0 \)): The distribution of blood type of COVID-19 patients is the same as the population. Any observed difference is not due to chance.
- Alternative Hypothesis (\( H_A \)): The distribution of blood type of COVID-19 patients is different from the population. Any observed difference is due to chance.
3. **Primary Variable Contribution:**
- Identify which blood type (A or O) contributes more to the test statistic.
- Options:
- A. type A
- B. type O
4. **Calculate the Test Statistic:**
- Chi-square test statistic (\( \chi^2 \)) calculation input field.
- \( \chi^2 = \) [Input Field]
5. **Degrees of Freedom:**
- State the degrees of freedom for this test.
- \( df = \) [Input Field]
6. **Calculate the p-value:**
- Input field to calculate the p-value for this test.
- \( p = \) [Input Field]
7. **Result Interpretation:**
- Based on the above p-value, select the strength of evidence against the null hypothesis.
- Options:
- [Dropdown] Strong evidence
This set of data aids in understanding how to apply statistical methods to compare categorical data distributions, specifically using chi-square tests to evaluate observed vs. expected frequency distributions.
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