The United States has an influenza season where more people than usual suffer from the flu. Some people, particularly those in vulnerable populations, develop serious complications and end up in the hospital. Hospitals and clinics need additional staff to adequately treat these extra patients. The medical staffing agency provides this temporary staff.

As a Data Analyst I will submit a recommendation, present insights to stakeholders in an easily consumable format to the medical agency to determine when to send staff to each state for the flu season of 2017.

Using storytelling create a report in Tableau telling the analytical story.

This is a project I did as part of a course in data analytics at Career Foundry.

1. Influenza deaths by geography, time, age, and gender Source: CDC Download Data Set
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‍2. Population data by geography Source: US Census Bureau Download Data Set
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‍3. Counts of influenza laboratory test results by state (survey) Source: CDC (Fluview) Download Influenza Visits Data Set
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‍Download Lab Tests Data Set
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1. Outline the possible bias from each of the datasets
2. Data Profiling and data cleaning (quality and integrity checks)
3. Data Integration and transformation
4. Formulate a Hypothesis test to compare if there is a significant difference regarding certain groups
5. Calculate the variance and standard deviation for key variables
6. Identify variables with a potential relationship and test for a correlation. Example, The correlation between deaths and population over 85+.
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Populations aged 65 and above are at higher risk from dying from influenza. This group accounts of majority of influenza death between 2009 to 2019.

Further analysis shows that states with larger elderly populations account for more influenza deaths. California, Texas New York, and Florida are states with largest vulnerable populations, which leads to highest number of influenza-related deaths.
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Most deaths occur during the winter period. Deaths generally begins in October and peak in December, January, and February. Flu season slows down in springtime.
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