Concerns have been raised about the effectiveness of this season's flu vaccination after it was noticed...

 

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Concerns have been raised about the effectiveness of this season's flu vaccination after it was noticed that a high proportion of people with severe illness have been vaccinated. Data has been collected on the following attributes of the flu sufferers (see the file Fluvac.xls). An identification number for the individual with flu The person's age in years VAC STATUS Whether or not the person has been vaccinated against the flu The severity of the illness (mild or severe) SEVERITY AGE CAT A categorical version of the age variable with 5 bins (0-20, 21-40, 41-60, 61-80, 80+) Your role is to investigate the data to determine if vaccination is effective or not. ID AGE 1. What percentage of vaccinated and unvaccinated people experience severe illness? [1 mark] 2. What is the average age of patients that are severely ill compared to patients with mild illness? [1 mark] 3. What is the average age of people that are vaccinated compared to people that are unvaccinated? [1 mark] 4. What proportion of people in the age category 41-60 are vaccinated? [1 mark] 5. Is there any age category where a higher proportion of vaccinated people are severely ill compared unvaccinated people? [1 mark] 6. Based on your investigation of the data set create two well-formatted tables that illustrate some important features of the data. Your tables should have informative labels and a readable number of decimal places. Each table should include an informative caption. 7. With reference to the tables you have made, explain if there is evidence that the vaccine is effective or not? 8. One reason why it is difficult to ascertain cause and effect based on association is that there may be confounding variables, these are variables which are related to both the explanatory (independent) and response (dependent) variable. In the data set presented here which variable is explanatory, which is response, and which is confounding? 9. Imagine that the data is this study has been collected by surveying people who present at hospital with flu symptoms. Can you identify any potential biases in this form of data collection that might influence our ability to answer our key question? How else could data be collected to avoid this bias? Concerns have been raised about the effectiveness of this season's flu vaccination after it was noticed that a high proportion of people with severe illness have been vaccinated. Data has been collected on the following attributes of the flu sufferers (see the file Fluvac.xls). An identification number for the individual with flu The person's age in years VAC STATUS Whether or not the person has been vaccinated against the flu The severity of the illness (mild or severe) SEVERITY AGE CAT A categorical version of the age variable with 5 bins (0-20, 21-40, 41-60, 61-80, 80+) Your role is to investigate the data to determine if vaccination is effective or not. ID AGE 1. What percentage of vaccinated and unvaccinated people experience severe illness? [1 mark] 2. What is the average age of patients that are severely ill compared to patients with mild illness? [1 mark] 3. What is the average age of people that are vaccinated compared to people that are unvaccinated? [1 mark] 4. What proportion of people in the age category 41-60 are vaccinated? [1 mark] 5. Is there any age category where a higher proportion of vaccinated people are severely ill compared unvaccinated people? [1 mark] 6. Based on your investigation of the data set create two well-formatted tables that illustrate some important features of the data. Your tables should have informative labels and a readable number of decimal places. Each table should include an informative caption. 7. With reference to the tables you have made, explain if there is evidence that the vaccine is effective or not? 8. One reason why it is difficult to ascertain cause and effect based on association is that there may be confounding variables, these are variables which are related to both the explanatory (independent) and response (dependent) variable. In the data set presented here which variable is explanatory, which is response, and which is confounding? 9. Imagine that the data is this study has been collected by surveying people who present at hospital with flu symptoms. Can you identify any potential biases in this form of data collection that might influence our ability to answer our key question? How else could data be collected to avoid this bias? Concerns have been raised about the effectiveness of this season's flu vaccination after it was noticed that a high proportion of people with severe illness have been vaccinated. Data has been collected on the following attributes of the flu sufferers (see the file Fluvac.xls). An identification number for the individual with flu The person's age in years VAC STATUS Whether or not the person has been vaccinated against the flu The severity of the illness (mild or severe) SEVERITY AGE CAT A categorical version of the age variable with 5 bins (0-20, 21-40, 41-60, 61-80, 80+) Your role is to investigate the data to determine if vaccination is effective or not. ID AGE 1. What percentage of vaccinated and unvaccinated people experience severe illness? [1 mark] 2. What is the average age of patients that are severely ill compared to patients with mild illness? [1 mark] 3. What is the average age of people that are vaccinated compared to people that are unvaccinated? [1 mark] 4. What proportion of people in the age category 41-60 are vaccinated? [1 mark] 5. Is there any age category where a higher proportion of vaccinated people are severely ill compared unvaccinated people? [1 mark] 6. Based on your investigation of the data set create two well-formatted tables that illustrate some important features of the data. Your tables should have informative labels and a readable number of decimal places. Each table should include an informative caption. 7. With reference to the tables you have made, explain if there is evidence that the vaccine is effective or not? 8. One reason why it is difficult to ascertain cause and effect based on association is that there may be confounding variables, these are variables which are related to both the explanatory (independent) and response (dependent) variable. In the data set presented here which variable is explanatory, which is response, and which is confounding? 9. Imagine that the data is this study has been collected by surveying people who present at hospital with flu symptoms. Can you identify any potential biases in this form of data collection that might influence our ability to answer our key question? How else could data be collected to avoid this bias?

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1 To determine the percentage of vaccinated and unvaccinated people experiencing severe illness the data from the FluVacxls file is required Unfortuna... View the full answer