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2 Patient Zero The COVID-19 pandemic was full of statistics, both good and bad. Someone close to us recently tried to make me into one of those statistics, which got me to pull out my old epidemiology datasets. As you probably recall, things looked bleak in March of 2020, but our concerns were soon dismissed by a scientist from Pfizer, who claimed to have developed a vaccine that was 90% effective. This scientist rushed into the office of the CEO to present the findings, and the CEO asked for a second analysis to be done to confirm the results of the study. Suppose the CEO sent a second scientist to Charger Union to sample every tenth student who walked in. This scientist ended up taking data from 33 patients, all of whom were given a vaccine and then exposed to the virus. These data are logged in the [COVID] sheet, which contains one column of data on the treatment outcomes (Treatment Outcome). If the vaccine prevented infection in a patient, then a value of 1 was recorded for that patient. If the vaccine failed, then a value of 0 was recorded. Write an executive summary for the CEO that addresses the following: 1. Describe the sampling structure (random, biased, stratified, inadequate, etc.). Are there any major issues with this study design that could have a bearing on the results? 2. Describe the level of information contained by the data (e.g., nominal, discrete, etc.). 3. Which distribution is the best choice to use to model these data? 1. Evaluate the claim of 90% efficacy. Is it true? Is it even close? What does "close" mean to you in this context, and how can we statistically arrive at an answer? 5. Since these data are coming from a sample, we can only estimate the true efficacy. Estimate the true efficacy. How certain are you that your estimation is correct? If applicable, justify the confidence level used in your analysis why did you pick it? 6. Is there an action that the company could take to get more conclusive results? Be sure to address any pushback that the CEO might have against your proposal.

2 Patient Zero The COVID-19 pandemic was full of statistics, both good and bad. Someone close to us recently tried to make me into one of those statistics, which got me to pull out my old epidemiology datasets. As you probably recall, things looked bleak in March of 2020, but our concerns were soon dismissed by a scientist from Pfizer, who claimed to have developed a vaccine that was 90% effective. This scientist rushed into the office of the CEO to present the findings, and the CEO asked for a second analysis to be done to confirm the results of the study. Suppose the CEO sent a second scientist to Charger Union to sample every tenth student who walked in. This scientist ended up taking data from 33 patients, all of whom were given a vaccine and then exposed to the virus. These data are logged in the [COVID] sheet, which contains one column of data on the treatment outcomes (Treatment Outcome). If the vaccine prevented infection in a patient, then a value of 1 was recorded for that patient. If the vaccine failed, then a value of 0 was recorded. Write an executive summary for the CEO that addresses the following: 1. Describe the sampling structure (random, biased, stratified, inadequate, etc.). Are there any major issues with this study design that could have a bearing on the results? 2. Describe the level of information contained by the data (e.g., nominal, discrete, etc.). 3. Which distribution is the best choice to use to model these data? 1. Evaluate the claim of 90% efficacy. Is it true? Is it even close? What does "close" mean to you in this context, and how can we statistically arrive at an answer? 5. Since these data are coming from a sample, we can only estimate the true efficacy. Estimate the true efficacy. How certain are you that your estimation is correct? If applicable, justify the confidence level used in your analysis why did you pick it? 6. Is there an action that the company could take to get more conclusive results? Be sure to address any pushback that the CEO might have against your proposal.

Principles of Information Systems (MindTap Course List)
Principles of Information Systems (MindTap Course List)
13th Edition
ISBN:9781305971776
Author:Ralph Stair, George Reynolds
Publisher:Ralph Stair, George Reynolds
Chapter9: Business Intelligence And Analytics
Section: Chapter Questions
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2 Patient Zero The COVID-19 pandemic was full of statistics, both good and bad. Someone close to us recently tried to make me into one of those statistics, which got me to pull out my old epidemiology datasets. As you probably recall, things looked bleak in March of 2020, but our concerns were soon dismissed by a scientist from Pfizer, who claimed to have developed a vaccine that was 90% effective. This scientist rushed into the office of the CEO to present the findings, and the CEO asked for a second analysis to be done to confirm the results of the study. Suppose the CEO sent a second scientist to Charger Union to sample every tenth student who walked in. This scientist ended up taking data from 33 patients, all of whom were given a vaccine and then exposed to the virus. These data are logged in the [COVID] sheet, which contains one column of data on the treatment outcomes (Treatment Outcome). If the vaccine prevented infection in a patient, then a value of 1 was recorded for that patient. If the vaccine failed, then a value of 0 was recorded. Write an executive summary for the CEO that addresses the following:
Transcribed Image Text:2 Patient Zero The COVID-19 pandemic was full of statistics, both good and bad. Someone close to us recently tried to make me into one of those statistics, which got me to pull out my old epidemiology datasets. As you probably recall, things looked bleak in March of 2020, but our concerns were soon dismissed by a scientist from Pfizer, who claimed to have developed a vaccine that was 90% effective. This scientist rushed into the office of the CEO to present the findings, and the CEO asked for a second analysis to be done to confirm the results of the study. Suppose the CEO sent a second scientist to Charger Union to sample every tenth student who walked in. This scientist ended up taking data from 33 patients, all of whom were given a vaccine and then exposed to the virus. These data are logged in the [COVID] sheet, which contains one column of data on the treatment outcomes (Treatment Outcome). If the vaccine prevented infection in a patient, then a value of 1 was recorded for that patient. If the vaccine failed, then a value of 0 was recorded. Write an executive summary for the CEO that addresses the following:
1. Describe the sampling structure (random, biased, stratified, inadequate, etc.). Are there any major issues with this study design that could have a bearing on the results? 2. Describe the level of information contained by the data (e.g., nominal, discrete, etc.). 3. Which distribution is the best choice to use to model these data? 1. Evaluate the claim of 90% efficacy. Is it true? Is it even close? What does "close" mean to you in this context, and how can we statistically arrive at an answer? 5. Since these data are coming from a sample, we can only estimate the true efficacy. Estimate the true efficacy. How certain are you that your estimation is correct? If applicable, justify the confidence level used in your analysis why did you pick it? 6. Is there an action that the company could take to get more conclusive results? Be sure to address any pushback that the CEO might have against your proposal.
Transcribed Image Text:1. Describe the sampling structure (random, biased, stratified, inadequate, etc.). Are there any major issues with this study design that could have a bearing on the results? 2. Describe the level of information contained by the data (e.g., nominal, discrete, etc.). 3. Which distribution is the best choice to use to model these data? 1. Evaluate the claim of 90% efficacy. Is it true? Is it even close? What does "close" mean to you in this context, and how can we statistically arrive at an answer? 5. Since these data are coming from a sample, we can only estimate the true efficacy. Estimate the true efficacy. How certain are you that your estimation is correct? If applicable, justify the confidence level used in your analysis why did you pick it? 6. Is there an action that the company could take to get more conclusive results? Be sure to address any pushback that the CEO might have against your proposal.
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